]>
2011
2
4
150
Robust Control of Dc Motor Using Fuzzy Sliding Mode Control and Genetic Algorithm
Robust Control of Dc Motor Using Fuzzy Sliding Mode Control and Genetic Algorithm
en
en
Wide amplitude, DC motor's speed and their facile control cause its great application in industries. Generally the DC motors gain speed by armature voltage control or field control. In this paper, by using a combination of Fuzzy Sliding Mode methods and Genetic Algorithms, we have tired to optimally control the inverted pendulum by nonlinear equations. The results of this simulation have been mentioned in the conclusion. It seems that the results be acceptable results.
572
579
Mahbubeh
Moghaddas
Mohamad Reza
Dastranj
Nemat
Changizi
Modjtaba
Rouhani
Nonlinear control
Optimal
classical PID controller
Genetic Algorithm
Article.1.pdf
[
[1]
S. Hwang, J. Chou, Comparison on fuzzy logic and PID controls for a DC motor position controller, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting, Denver (1994)
##[2]
J. Tang, R. Chassaing, PID Controller Using theTMS320C31 DSK for Real-Time DC Motor Control, Proceedings of the 1999 Texas Instruments DSPS Fest, Houston (1999)
##[3]
Y. P. Yang, C. H. Cheung, S. W. Wu, J. P. Wang, Optimal design and control of axial-flux brushless dc wheel motor for electrical vehicles, Proceedings of the 10th Mediterranean Conference on Control and Automation-MED2002, Lisbon (2002)
##[4]
H. C. Cho, K. S. Lee, M. S. Fadali, Real-time adaptive speed control of dc motors with bounded periodic random disturbance, International Journal of Innovative Computing, Information and Control, 5 (2009), 2575-2584
##[5]
M. Fallahi, S. Azadi, Adaptive Control of a DC Motor Using Neural Network Sliding Mode Control, Proceedings of the International Multi Conference of Engineers and Computer Scientists, Hong Kong (2009)
##[6]
J. S. R. Jang, ANFIS: adaptive-network-based fuzzy inference system, IEEE Trans. syst. man cybern., 23 (1993), 665-685
##[7]
B. Allaoua, A. Laoufi, B. Gasbaoui, A. Abderrahmani, Neuro-fuzzy DC motor speed control using particle swarm optimization, Leonardo Electronic Journal of Practices and Technologies, 15 (2009), 1-18
##[8]
M. Fallahi, S. Azadi, Robust Control of DC Motor Using Fuzzy Sliding Mode Control with PID Compensator, Proceedings of the International Multi Conference of Engineers and Computer Scientists, Hong Kong (2009)
]
A Novel Algorithm for Finding Equilibrium Strategy in Two Person Zero Sum Game with Fuzzy Strategy Sets and Payoffs
A Novel Algorithm for Finding Equilibrium Strategy in Two Person Zero Sum Game with Fuzzy Strategy Sets and Payoffs
en
en
This paper investigates a two person zero sum matrix game in which the payoffs and strategy are characterized as random fuzzy variables. Using the operations of triangular fuzzy numbers, the fuzzy payoffs for all synthetic outcomes are calculated. Based on random fuzzy expected value operator, a random fuzzy expected minimax equilibrium strategy to the game is defined. After that, based on the constraints, the feasible strategy string sets of the players for multi conflict situations are constructed. Then an iterative algorithm based on random fuzzy simulation is designed to seek the minimax equilibrium strategy. Using a linear ranking function, the aggregation model can be solved by transforming it into a crisp bimatrix game. Then, the fuzzy synthetic aggregation model is established and solved by transforming it into a crisp bimatrix game. Finally, a military example is provided to illustrate the practicality and effectively of the model.
580
587
Seyyed Mohammad Reza
Farshchi
Gelare
Veisi
Taghi
Karimi
Morteza
Aghaei
Fuzzy game theory
two person game
equilibrium strategy
fuzzy payoff.
Article.2.pdf
[
[1]
O. Morgenstern, J. Von Neumann, Theory of Games and Economic Behavior, Princeton university press, U.S.A. (1944)
##[2]
J. Berg, A. Engel, Matrix games, mixed strategies, and statistical mechanics, Phys. Rev. Lett., 81 (1998), 4999-5002
##[3]
L. Ein-Dor, I. Kanter, Matrix games with non uniform payoff distributions, Physica A: Statistical Mechanics and its Applications, 302 (2001), 80-88
##[4]
L. A. Zadeh, Fuzzy Sets, Information and Control, 8 (1965), 338-353
##[5]
L. Campos, Fuzzy linear programming models to solve fuzzy matrix games, Fuzzy Sets and Systems, 32 (1989), 275-289
##[6]
I. Nishizaki, M. Sakawa, Fuzzy and Multi objective Games for Conflict Resolution, Springer-Verlag, Heidelberg (2001)
##[7]
C. R. Bector, S. Chandra, V. Vijay, Duality in linear programming with fuzzy parameters and matrix games with fuzzy payoffs, Fuzzy Sets and Systems, 146 (2004), 253-269
##[8]
V. Vijay, S. Chandra, C. R. Bector, Matrix games with fuzzy goals and fuzzy payoffs, Omega, 33 (2005), 425-429
##[9]
H. Kwarkernaak, Fuzzy random variables--I: definitions and theorems, Information Sciences, 15 (1978), 1-29
##[10]
H. Kwakernaak, Fuzzy random variables--II: Algorithms and examples for the discrete case, Information Sciences, 17 (1979), 253-278
##[11]
M. Puri, D. Ralescu, Fuzzy random variables, Journal of Mathematical Analysis and Applications, 114 (1986), 409-422
##[12]
Y. K. Liu, B. Liu, Expected value operator of random fuzzy variable and random fuzzy expected value models, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11 (2003), 195-215
##[13]
Y. Yoshida, A stopping game in a stochastic and fuzzy environment, Mathematical and Computer Modeling, 30 (1999), 147-158
##[14]
Y. K. Liu, B. Liu, Fuzzy random variables: a scalar expected value, Fuzzy Optimization and Decision Making, 2 (2003), 143-160
##[15]
L. Xu, R. Zhao, Y. Ning, Two person zero sum matrix game with fuzzy random payoffs, International Conference on Intelligent Computing, 2006 (2006), 809-818
##[16]
B. Liu, B. Liu, Theory and Practice of Uncertain Programming, Springer-Verlag, Heidelberg (2002)
]
Closedness of the Rang of the Product of Projections in Hilbert Modules
Closedness of the Rang of the Product of Projections in Hilbert Modules
en
en
Suppose P and Q are orthogonal projections between Hilbert C*-modules, then
PQ has closed range if and only if Ker(P)+Ran(Q) is an orthogonal summand,
Ker(Q)+ Ran(P) is an orthogonal summand.
588
593
Kamran
Sharifi
Hilbert C*-module
projection
Moore-Penrose inverse
closed range.
Article.3.pdf
[
[1]
R. Bouldin, The product of operators with closed range, Tôhoku Math. J., 25 (1973), 359-363
##[2]
R. Bouldin, Closed range and relative regularity for products, J. Math. Anal. Appl., 61 (1977), 397-403
##[3]
F. Deutsch, The angle between subspaces in Hilbert space, in: Approximation theory, wavelets and applications, 1995 (1995), 107-130
##[4]
M. Frank, K. Sharifi, Adjointability of densely defined closed operators and the Magajna-Schweizer Theorem, J. Operator Theory, 63 (2010), 271-282
##[5]
M. Frank, K. Sharifi , Generalized inverses and polar decomposition of unbounded regular operators on Hilbert C*-modules , J. Operator Theory, Vol. 64, 377--386 (2008)
##[6]
J. M. Gracia-Bonda, J. C. Várilly, H. Figueroa, Elements of noncommutative geometry, Birkhäuser, Boston (2000)
##[7]
S. Izumino, The product of operators with closed range and an extension of the revers order law, Tôhoku Math. J., 34 (1982), 43-52
##[8]
J. J. Koliha, The Drazin and Moore-Penrose inverse in C*-algebras, Proc. Roy. Irish Acad. Sect. A, 99 (1999), 17-27
##[9]
J. J. Koliha, V. Rakočević, Fredholm properties of the difference of orthogonal projections in a Hilbert space, Integr. Equ. Oper. Theory , 52 (2005), 125-134
##[10]
E. C. Lance , Hilbert C*-modules: a toolkit for operator algebraists, Cambridge University Press, Cambridge (1995)
##[11]
G. J. Murphy, C*-algebras and Operator Theory, Academic Press, New York (1990)
##[12]
I. Raeburn, D. P. Williams, Morita Equivalence and Continuous Trace C*-algebras, American Mathematical Soc., Providence (1998)
##[13]
K. Sharifi, Descriptions of partial isometries on Hilbert C*-modules, Linear Algebra Appl., 431 (2009), 883-887
##[14]
K. Sharifi , Groetsch’s Representation of Moore-Penrose inverses and illposed problems in Hilbert C*-modules, J. Math. Anal. Appl., 365 (2010), 646-652
##[15]
Q. Xu, L. Sheng, Positive semi-definite matrices of adjointable operators on Hilbert C*-modules, Linear Algebra Appl., 428 (2008), 992-1000
]
Evaluation of Science and Technology Parks by Using Fuzzy Expert System
Evaluation of Science and Technology Parks by Using Fuzzy Expert System
en
en
The science parks have important role in development of technology and are able to make economic growth of the countries. The purpose of this article is the presentation of a fuzzy expert system to evaluate the science and technology parks. One of the problems for evaluating Science and Technology parks is to have the high number of criteria and science parks and presenting a system which is able to compare this high number of science parks, with many criteria, is one of the findings of this paper. At the end, we have described a numerical example. This article is an useful information resource for managers of Science and Technology parks and interested parties to invest and to recognize the science parks better.
594
606
Hamid
Eslami Nosratabadi
Sanaz
Pourdarab
Mohammad
Abbasian
Science and technology parks
Fuzzy expert systems
Fuzzy logic
Article.4.pdf
[
[1]
P. Escorsa, J. Valls , A proposal for a typology of science parks, Technopolis Brighton, U. K. (1996)
##[2]
B. Bigliardi, A. I. Dormio, A. Nosella, G. Petroni, Assessing science parks performances: directions from selected Italian case studies, Technovation, 26 (2006), 489-505
##[3]
C. J. Chen, H. L. Wu, B. W. Lin, Evaluating the development of high-tech industries:Taiwan’ s science park, Technological Forcasting & Social Change, 73 (2006), 452-465
##[4]
R. Joseph, New ways to make technology parks more relevant, Prometheus, 12 (1994), 46-61
##[5]
S. Mian, Assessing value added contributions of university technology business incubators to tenant firms, Research Policy, 25 (1996), 325-335
##[6]
F. Cesaroni, A. Gambardella, Dai contenitori ai contenuti: i parchi scientifici e tecnologici in Italia, Fondazione Agnelli, Italy (1988)
##[7]
P. Formica, La cooperazione universita`-industria nei parchi scientifici e tecnologici, Primo Convegno nazionale APSTI, Genova (1992)
##[8]
P. Formica, Mutanti aziendali : imprese, centri di innovazione e parchi scientifici nell'era tecnopolitana, CUEN, Napoli (1994)
##[9]
H. Lofsten, P. Lidelof, Science parks in Sweden industrial renewal and development, R&D Management, 31 (2001), 309-322
##[10]
A. Richne, S. Jacobsson, New technology based firms in Sweden a study of their impact on industrial renewal, Economics of innovation and new technology, 3 (1999), 197-223
##[11]
M. Chorda, Towards the maturity stage: an insight into the performance of French technopoles, Technovation, 16 (1996), 143-152
##[12]
D. J. Storey, B. S. Tether, Public policy measures to support new technology based firms in the European Union, Research policy, 26 (1998), 1037-1057
##[13]
Y. l. Bakouros, D. C. Mardas, N. C. Varsakelis, Science park, a high tech fantasy?: an analysis of the science parks of Greece, Technovation, 22 (2002), 123-128
##[14]
E. Turban, J. E. Aronson, T. P. Liang, Decision Support Systems and Intelligent Systems, Prentice-Hall, New Delhi (2004)
##[15]
H. J. Shyur, H. S. Shih, A hybrid MCDM model for strategic vendor selection, Mathematical and Computer modeling, 44 (2006), 749-761
##[16]
T. J. Ross, Fuzzy logic with engineering applications, John Wiley & Sons, New York (2004)
##[17]
C. C. Koha Francis, T. H. Kohb Winston, An analytical framework for science parks and technology ,districts with an application to Singapore, School of Economics and Social Sciences, 20 (2005), 217-239
##[18]
D. Felsenstein, University-related science parks--seedbeds’ or enclaves of innovation? , Technovation , 14 (1994), 93-110
##[19]
J. Choi, CIMS, North Carolina State University, U.S.A. (2004)
##[20]
D. Siegel, P. Westhead, M. Wright, Science parks and the performance of new technology – based firms: A review of recent UK evidence and an agenda for future research, Small Business Economics, 20 (2003), 177-184
##[21]
L. Hommen, D. Doloreux, E. Larsson, Emergence and Growth of Mjärdevi Science Park in Linköping, European Planning Studies, 14 (2006), 1331-1361
##[22]
H. Amirahmadi, G. Staff, Science parks: a critical assessment, Journal of Planning Literature, 8 (1993), 107-123
##[23]
J. Currie, Science parks in Britain: Their role for the late 1980's, CSP Economic Publications, Cardiff (1985)
##[24]
F. M. Eul, Science parks and innovation centres—property, the unconsidered element. Science Parks and Innovation Centres: Their Economic and Social Impact, Elsevier, Amsterdam (1985)
##[25]
D. Doloreux, Technopoles et trajectoires stratégiques: Le cas de la ville de Laval (Québec), Cahiers de Géographie du Québec, 43 (1999), 211-235
##[26]
C. S. P. Monck, R. B. Porter, P. Quintas, D. J. Storey, P. Wynarczyck, Science parks and the growth of high technology firms, Croom Helm, London (1988)
##[27]
P. Nijkamp, G. Oirschot Van, A. Oosterman, Knowledge Networks, Science Parks and Regional Development: An International Comparative Analysis of Critical Success Factors, in: An international comparative analysis of critical success factors: Moving frontiers: Economic restructuring, regional development, and emerging networks, 1994 (1994), 225-246
##[28]
M. Quéré, Les technopoles et la notion de politique technologique régionale, In: Territoires et politiques technologiques: comparaisons régionales, 1996 (1996), 143-160
##[29]
J. Simmie, Innovation, networks and learning regions? , Jessica Kingsley Publishers, London (1997)
##[30]
International Association of Science Parks, , Science Park (IASP official definition), (2002)
##[31]
D. Durão, M. Sarmento, V. Varela, L. Maltez, Virtual and real-estate science and technology parks, Technovation, 25 (2005), 237-244
##[32]
C. J. Chen, C. C. Huang, A multiple criteria evaluation of high-tech industries for the scince-based industrial park in Taiwan, Information & Management, 41 (2004), 839-851
##[33]
D. Massey, P. Quintas, D. Wield, High Tech Fantasies: Science Parks in Society, Routhledge, London (1991)
##[34]
P. Westhead, D. J. Storey, Links between higher education institutions and high technology firms, Omega, 23 (1995), 345-360
##[35]
C. Vedovello, Science parks and university-industry interaction: geographical proximity between the agents as a driving force, Technovation, 17 (1997), 491-531
##[36]
J. Phillimore, Beyond the linear view of innovation in science park evaluation: An analysis of Western Australian Technology Park, Technovation, 19 (1999), 673-680
##[37]
W. H. Lee, W. T. Yang, The cradle of Taiwan high technology industry development--Hsinchu Science Park, Technovation, 20 (2000), 55-59
##[38]
M. Stefano, C. A. Magni, The use of fuzzy logic and expert systems for rating and pricing firms A new perspective on valuation, Managerial Finance, 33 (2007), 836-852
##[39]
H. Fazlollahtabar, H. Eslami, H. Salmani, Designing a Fuzzy Expert System to Evaluate Alternatives in Fuzzy Analytic Hierarchy Process, Journal of Software Engineering and Applications, 3 (2010), 409-418
##[40]
M. Schneider, G. Langholz, A. Kandel, G. Chew, Fuzzy Expert System Tools, John Wiley & Sons, New York (1996)
##[41]
E. H. Mamdani, S. Assilian, An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller, International Journal of Man-Machine Studies, 7 (1975), 1-13
##[42]
T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications of modeling and control, IEEE Transactions of Systems. Man and Cybernetics, 1985 (1985), 116-132
##[43]
H. Sydenham, R. Thorn, Handbook of Measuring System Design, Rule-based Expert Systems, John Wiley & Sons, U.S.A. (2005)
##[44]
O. Cordon, F. Herrera, F. Hoffmann, L. Magdalena, Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, World Scientific Publishing Company, Singapore (2001)
]
On Some Geometric Properties of the Sphere \(S^n\)
On Some Geometric Properties of the Sphere \(S^n\)
en
en
It is known that the sphere \(S^n\) admits an almost complex structure only when
\(n = 2\) or \(n = 6\) . In this paper, we show that the sphere \(S^n\) is a space of
constant sectional curvature and using the results of T. Sato in [4], we
determine the scalar curvature and the *-scalar curvature of \(S^6\). We shall also
prove that \(S^6\) is a non-Kähler nearly Kähler manifold using the Levi-Civita
connection on \(S^6\) defined by H. Hashimoto and K. Sekigawa [3]. In [2], A. Gray
and L. Hervella defined sixteen classes of almost Hermitian manifolds. We shall
define quasi-Hermitian, a class of almost Hermitian manifolds and partially
characterize almost Hermitian manifolds that belong to this class. Finally,
under certain conditions, we shall show the sphere \(S^6\) is quasi-Hermitian.
607
618
Richard S.
Lemence
Dennis T.
Leyson
Marian P.
Roque
Sphere
Kähler manifolds
Hermitian manifolds
quasi- Hermitian manifolds
Article.5.pdf
[
[1]
A. Newlander, L. Nirenberg , Complex Analytic Coordinates in Almost Complex Manifolds , Annals of Mathematics, 2 (1957), 391-404
##[2]
A. Gray, L. M. Hervella, The sixteen classes of almost Hermitian manifolds and their linear invariants, Annali di Matematica, 123 (1980), 35-58
##[3]
H. Hashimoto, K. Sekigawa, Submanifolds of a nearly-Kähler 6- dimensional sphere, Proceedings of the Eighth International Workshop on Differential Geometry, 2004 (2004), 23-45
##[4]
T. Sato, Curvatures of almost Hermitian manifolds, Graduate School of Science and Technology (Doctoral Thesis), 1--84 (1992)
##[5]
B. S. Kruglikov , Nijenhuis tensors and obstructions for pseudoholomorphic mapping constructions, University of Tromso, 1996 (1996), 1-43
]
Using the Fuzzy AHP Methodology in Customer's Purchasing Decision-making Process Based on Marketing Mix (4Ps)
Using the Fuzzy AHP Methodology in Customer's Purchasing Decision-making Process Based on Marketing Mix (4Ps)
en
en
In purchasing process, whether in traditional or online, we face the problem of comparison and decision-making. Also given the fact that the main criteria which are considered by most customers in purchasing process are marketing mix (4Ps), so we take into consideration these criteria as the main criterion. Moreover, lack of certainty and definability of these criteria in fuzzy form lead us to model customer’s purchasing decision-making process by using the fuzzy AHP methodology.
619
630
Basirat
Baygi. Mojtaba
Emam. Seyed
Reza
Fuzzy AHP
Marketing Mix (4Ps)
Customer’s Purchasing Decision-Making Process
Article.6.pdf
[
[1]
J. Cha, S. Kim, Y. Lee, Application of multi dimensional scaling for marketing-mix modification: A case study on mobile phone category, Expert Syst. Appl., Vol. 36, 4884--4890 (2008)
##[2]
P. Kotler, Marketing In The Twenty-First Century, in: Marketing Management, New Jersey (2001)
##[3]
M. Zineldin, S. Philipson, Kotler and Borden are not dead: myth of Relationship marketing and truth of the 4Ps, Journal of consumer marketing, Vol. 24, 229--241 (2007)
##[4]
C. Vignali, McDonald's:“think global, act local”–the marketing mix, British Food Journal, Vol. 103, 97--111 (2001)
##[5]
C. A. Chen, Information–Oriented Online Shopping Behavior in Electronic Commerce Environment , JournalL of Sofrware (JSW), 4 (2009), 307-315
##[6]
S. Mohebbi, R. Shafaei, e-Supply network coordination: the design of intelligent agents for buyer – supplier dynamic negotiations, Journal of intelligent Manufacturing, Vol. 23, 375--391 (2012)
##[7]
I. Mahdavi, S. Mohebbi, M. Zandakbari, N. Cho, N. Mahdavi-Amiri, Agent-based web service for the design of a dynamic coordination Mechanism in supply networks, Journal of Intelligent Manufacturing, Vol. 20, 727--749 (2009)
##[8]
S. Koul, R. Verma, Dynamic Vendor Selection: A Fuzzy AHP Approch, International Journal of the Analytic Hierarchy Process, Vol. 4, 118--136 (2012)
##[9]
T. L. Saaty, The Analytical Hierarchy Process, RWS publication, Pittsburg (1980)
##[10]
G. Barbarosoglu, T. Yazgac, An application of the analytic hierarchy process to the supplier selection problem , Production and Inventory Management Journal, 38 (1997), 14-21
##[11]
R. E. Bellman, L. A. Zadeh, Decision-making in a fuzzy environment, Management Sciences, 17 (1970), 141-164
##[12]
H. J. Zimmermann, Fuzzy Set Theory and Its Applications, Kluwer Academic Publishers, Dordrecht (1991)
##[13]
J. J. Buckley, T. Feuring, Y. Hayashi, Fuzzy hierarchical analysis revisited, Eur. J. Oper. Res., 129 (2001), 48-64
##[14]
S. Zaim, M. Sevkli, M. Tarim, Fuzzy Analytic Hierarchy Based Approach for Supplier Selection, Journal of Euromarketing, 12 (2003), 147-176
##[15]
C. T. Chen, C. T. Lin, S. F. Huang, A fuzzy approach for supplier evaluation and selection in supply chain management , Int. J. Prod. Econ., 102 (2006), 289-301
##[16]
G. Noci, G. Toletti, Selecting quality-based programmes in small firms: A comparison between the fuzzy linguistic approach and the analytic hierarchy process, Int. J. Prod. Econ., 67 (2000), 113-133
##[17]
L. C. Leung, D. Cao, On consistency and ranking of alternatives in fuzzy AHP, Eur. J. Oper. Res., 124 (2000), 102-113
##[18]
D. Y. Chang, Application of the extent analysis method on fuzzy AHP, Eur. J. Oper. Res., 95 (1996), 649-655
]
Some Remarks on Manifolds with Vanishing Bochner Tensor
Some Remarks on Manifolds with Vanishing Bochner Tensor
en
en
In this paper, we present our results on Einsteinian, almost Hermitian manifolds with Bochner tensor B = 0. It shall be shown that under some conditions, these Bochner flat manifolds are complex space forms. Moreover, they are also Kähler manifolds with a constant holomorphic sectional curvature. We also present an identity for the Riemannian curvature of a generalized complex space form.
631
638
Eileen May G.
Cariaga
Richard S.
Lemence
Marian P.
Roque
Complex space forms
Kähler manifolds
Bochner tensor
generalized complex space forms
Article.7.pdf
[
[1]
T. Koda, Self-dual and anti-Self-dual Hermitian Surfaces, Kodai Math. J., 10 (1987), 335-342
##[2]
T. Koda, K. Sekigawa, Self-Dual Einstein Hermitian Surfaces, Advanced Studies in Pure Mathematics, 22 (1993), 123-131
##[3]
R. S. Lemence, On Four-Dimensional Generalized Comples Space Forms, Nihonkai Math. J., 15 (2004), 169-176
##[4]
K. Matsuo, Pseudo-Bochner Curvature Tensor on Hermitian Manifolds, Colloquium Mathematicum, 80 (1999), 201-209
##[5]
K. Sekigawa, On some 4-dimensional compact almost Hermitian manifolds , J. Ramanujan Math. Soc., 2 (1987), 101-116
##[6]
K. Sekigawa, T. Koda, Compact Hermitian Surfaces of Pointwise Constant Holomorphic Sectional Curvature, Glasgow Math. J., 37 (1994), 343-349
##[7]
S. Tachibana, On the Bochner Curvature Tensor, Natural Science Report, Ochanomizu University, 18 (1967), 15-19
##[8]
S. Tachibana, R. C. Liu, Notes on Kahlerian Metrics with Vanishing Bochner Curvature Tensor, Kodai Math. Sem. Rep., 22 (1970), 313-321
##[9]
F. Tricerri, L. Vanhecke, Curvature Tensors on Almost Hermitian Manifolds, Transactions of the American Mathematical Society, 267 (1981), 365-398
##[10]
L. Vanhecke, The Bochner curvature tensor on almost Hermitian manifolds, Rend. Sem. Mat. Univ. Politec. Torino, 34 (1975/76), 21-38
##[11]
L. Vanhecke, On the Decomposition of curvature tensor fields on almost Hermitian manifolds, Proc. Conf. Differential Geometry (Michigan State University), 1976 (1976), 16-33
##[12]
L. Vanhecke, F. Bouten, Constant type for almost Hermitian manifolds, Bulletin mathématique de la Société des Sciences Mathématiques de la République Socialiste de Roumanie, 20 (1976), 415-422
]
Optimal Control of HIV Infection by Using Fuzzy Dynamical Systems
Optimal Control of HIV Infection by Using Fuzzy Dynamical Systems
en
en
A dynamical system represent the infection and propagation of HIV is considered. First a mathematical
model for the HIV is simulated. Since age, sex… are important parameters in treatment of HIV disease,
it is natural to consider the variables as fuzzy variables. Thus we need to consider a fuzzy dynamical
system to control the HIV disease. To solve such a fuzzy dynamical system, by using α-cuts, one can
convert this system to a non-fuzzy system of differential equations, then by using numerical methods
one may attempts to solve these differential equations
639
649
M.
Najariyan
M. H.
Farahi
M.
Alavian
Fuzzy differential equations
nonlinear programming
discretization method
HIV
Article.8.pdf
[
[1]
M. A. Nowak, R. M. May, Mathematical biology of HIV infections, Antigenic variation and diversity threshold, Mathematical Biosciences, 106 (1991), 1-21
##[2]
A. N. W .Hone, Painleve tests, singularity structure and integrability, arXiv.org , 2005 (2005), 1-34
##[3]
M. A. Capistran, F. J. Solis, On the modeling of long-term HIV-1 infection dynamics, Mathematical and computer modeling, 50 (2009), 777-782
##[4]
M. A. Nowak, R. M. May, Virus dynamics, Oxford University Press, Oxford (2000)
##[5]
A. S. Perelson, P. W. Nelson, Mathematical analysis of HIV-1 dynamics in vivo, SIAM review, 41 (1999), 3-44
##[6]
A. S. Perelson, Modeling the interaction of the immune system with HIV, in: Mathematical and statistical approaches to AIDS epidemiology, 350--370 (1989)
##[7]
A. S. Perelson, D. E. Kirschner, R. De Boer, Dynamics of HIV infection of \(CD4^+\) T cells, Mathematical biosciences, 114 (1993), 81-125
##[8]
P. K. Srivastava, P. Chandra, Modeling the dynamics of HIV and \(CD4^+\) T cells during primary infection, Nonlinear Analysis: Real World Applications, 11 (2010), 612-618
##[9]
L. M. Wein, S. A. Zenios, M. A. Nowak, Dynamics multidrug therapies for HIV: A theoretic approach, Journal of Theoretical Biology, 35 (1997), 15-29
##[10]
D. Kirschner, S. Lenhart, S. Serbin, Optimal control of the chemotherapy of HIV, Journal of Mathematical Biology, 35 (1997), 775-792
##[11]
M. J. Mhawej, C. H. Moog, F. Biafore, C. Francois, Control of the HIV infection and drug dosage, Biomedical Signal Processing and Control, 5 (2010), 45-52
##[12]
R. Jafelice, L. C. Barros, R. C. Bassanezi, F. Gomide, Fuzzy rules in asymptomatic HIV virus infected individuals model, Frontiers in Artifical Intelligence and Applications, 85 (2002), 208-215
##[13]
R. M. Jafelice, L. C. De Barros, R. C. Bassanezi, F. Gomide, Methodology to determine the evolution of asymptomatic HIV population using fuzzy set theory, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 13, 39--58 (2003)
##[14]
L. C. Barros, R. C. Bassanezi, M. B. Leite, The epidemiological models SI with fuzzy parameter of transmission, Comput. Math. Appl., 45 (2003), 1619-1628
##[15]
N. Ortega, L. C. Barros, E. Massad, Fuzzy gradual rules in epidemiology, Kyberentes: Int. J. Syst. Cybernetics, 32 (2003), 460-477
##[16]
V. Křivan, G. Colombo, A non-stochastic approach for modeling uncertainty in population dynamics, Bull. Math. Biol., Vol. 60, 721--751 (1998)
##[17]
P. Diamond, P. E. Kloeden, Metric spaces of fuzzy sets: theory and applications, World Scientific, Singapore (1994)
##[18]
M. L. Puri, D. Ralescu, Differentials of fuzzy functions, J. Math. Anal. Appl., 91 (1983), 552-558
##[19]
B. Bede, S. G. Gal, Generalizations of the differentiability of fuzzy-number-valued functions with applications to fuzzy differential equations, Fuzzy sets and systems, 151 (2005), 581-599
##[20]
Y. Chalco-Cano, H. Roman-Flores, One new solution of fuzzy differential equations, Chaos Solitons Fractals, 38 (2008), 112-119
##[21]
A. Khastan, F. Bahrami, K. Ivaz, New results on multiple solutions for nth-order fuzzy differential equations under generalized differentiability, Boundary value problems, 2009 (2009), 1-13
##[22]
Y. Chalco-Cano, H. Roman-Flores, On new solutions of fuzzy differential equations, Chaos Solitons Fractals, 38 (2008), 112-119
##[23]
J. J. Nieto, A. Khastan, K. Ivaz, Numerical solution of fuzzy differential equations under generalized differentiability, Nonlinear Analysis: Hybrid Systems, 3 (2009), 700-707
##[24]
K. P. Badakhshan, A. V. Kamyad, A. Azemi, Using AVK method to solve nonlinear problems with uncertain parameters, Applied Mathematics and Computation, 189 (2007), 27-34
]
Optimal Control of an HIV Model
Optimal Control of an HIV Model
en
en
We consider an HIV model, based on optimal control, for identifying the best treatment strategy in order to maximize the healthy cells by using chemotherapies with minimum side effects. In this paper, a new approach is introduced which transform the constraints of problem to the integral constraints. By an approximation, we obtain a finite dimensional linear programming problem which give us an approximate solution for original problem.
650
658
H. R.
Erfanian
M. H.
Noori Skandari
HIV Model
Optimal Control
Linear programming
Measure theory
Chemotherapy .
Article.9.pdf
[
[1]
A. A. Ejigu , An Efficient Treatment Strategy for HIV Patients Using Optimal Control, African Institute for Mathematical Sciences (AIMS), South Africa (2008)
##[2]
H. R. Erfanian, A. V. Kamyad, S. Effati , The optimal method for solving continuous linear and nonlinear programs, Applied mathematical sciences, 3 (2009), 1209-1217
##[3]
A. B. Gumel, P. N. Shivakumar, B. M. Sahai, A mathematical model for the dynamics of HIV-1 during the typical course of infection, Nonlinear Analysis, Theory, Methods and Applications, 47 (2001), 1773-1783
##[4]
A. Heydari, M. H. Farahi, A. A. Heydari, Chemotherapy in an HIV model by a pair of optimal control, Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization (Beijing, China), 2007 (2007), 58-63
##[5]
H. R. Joshi, Optimal control of an HIV immunology model, Optimal Control Applications and Methods, 23 (2002), 199-213
##[6]
J. Karrakchou, M. Rachik, S. Gourari, Optimal control and Infectiology: Application to an HIV/AIDS Model, Applied Mathematics and Computation, 177 (2006), 807-818
##[7]
A. V. Kamyad, J. E. Rubio, D. A. Wilson, An optimal control problem for the multidimensional diffusion equation with a generalized control variable, Journal of Optimization Theory and Applications, 75 (1992), 101-132
##[8]
A. V. Kamyad, J. E. Rubio, D. A. Wilson, The optimal control of the multidimensional diffusion equation, Journal of Optimization theory and Application, 70 (1991), 191-209
##[9]
J. E. Rubio, Control and Optimization the Linear Treatment of Non-linear Problems, Manchester University Press, Manchester (1986)
##[10]
H. Zarei, A. V. Kamyad, S. Effati, Maximizing of Asymptomatic Stage of Fast Progressive HIV Infected Patient Using Embedding Method Intelligent Control and Automation, Intelligent Control and Automation, 1 (2010), 48-58
]
Robust Control of Inverted Pendulum Using Fuzzy Sliding Mode Control (FSMC)
Robust Control of Inverted Pendulum Using Fuzzy Sliding Mode Control (FSMC)
en
en
Due to the vast application of inverted pendulum in robust, one of the most important Problems today is robotics and its control. In this paper by using fuzzy sliding control, we have tried to control the inverted pendulum angle by nonlinear equations. No oscillation in response in seen by using this method and the time for achieving a desirable response is appropriate. The results of this simulation have as well as its comparison with the classical controller has been mentioned at the conclusion.
659
666
Mohamadreza
Dastranj
Mahbubeh
Moghaddas
Kazem
Esmaeili Khoshmardan
Assef
Zare
nonlinear system
fuzzy control
sliding mode
artificial control
inverted pendulum
Article.10.pdf
[
[1]
N. Jia, H. Wang, Nonlinear Control of an Inverted Pendulum System based on sliding mode method, ACTA Analysis Functionalis applicata, 9 (2008), 234-237
##[2]
O. T. Altinoz, A. E. Yilmaz, Gerhard Wilhelm Weber Chaos Particle Swarm Optimized PID Controller for the Inverted Pendulum System, 2nd international conference on engineering optimization, Lisbon (2010)
##[3]
W. Wang, Adaptive Fuzzy Sliding Mode Control for Inverted Pendulum , Proceedings of the Second Symposium International Computer Science and Computational Technology (P. R. China), 2009 (2009), 231-234
##[4]
V. Sukontanakarn, M. Parnichkun, Real-Time Optimal Control for Rotary Inverted Pendulum, American Journal of Applied Science, 6 (2009), 1106-1115
##[5]
A. Bogdanov , Optimal Control of a Double Inverted Pendulum, Oregon Health and Science University (Tech. Rep.), Beaverton (2004)
##[6]
T. Sugie, K. Fujimoto, Controller design for an inverted pendulum based on approximate linearization, International Journal of Robust and Nonlinear Control: IFAC‐Affiliated Journal, 8 (1998), 585-597
##[7]
S. Horikawa, M. Yamaguchi, T. Furuhashi, Y. Uchikawa, Fuzzy control for inverted pendulum using fuzzy neural networks, JRM, Vol. 7, 36-44 (1995)
##[8]
I. H. Zadeh, S. Mobayen, PSO-based controller for balancing rotary inverted pendulum, J. Applied Sci., 16 (2008), 2907-2912
##[9]
Y. Becerikli, B. K. Celik, Fuzzy control of inverted pendulum and concept of stability using Java application, Mathematical and Computer Modeling, 46 (2007), 24-37
]
A Numerical Algorithm for Solving Nonlinear Fuzzy Differential Equations
A Numerical Algorithm for Solving Nonlinear Fuzzy Differential Equations
en
en
In this paper, we propose a numerical algorithm based on Runge-Kutta methods to and solution of nonlin-
ear fuzzy differential equations (FDEs) such that it solution satisffes solution found via differential inclusions. Our interpretation of the FDEs is a family of fuzzy differential inclusions. The method is illustrated by some examples.
667
671
M.
Rostami
M.
Kianpour
E.
Bashardoust
Nonlinear Fuzzy differential equations
Fuzzy differential inclusions
H-difference
Runge-Kutta methods.
Article.11.pdf
[
[1]
D. P. Datta, The golden mean, scale free extension of real number system, fuzzy sets and 1/f spectrum in physics and biology, Chaos Solitons Fractals, 17 (2003), 781-788
##[2]
M. S. El Naschie, From experimental quantum optics to quantum gravity via a fuzzy Kahler manifold, Chaos Solitons Fractals, 25 (2005), 969-977
##[3]
M. L. Puri, D. A. Ralescu, Differentials of Fuzzy Functions, J. Math. Anal. Appl., 91 (1983), 552-558
##[4]
B. Bede, S. G. Gal, Almost periodic fuzzy-number-valued functions, Fuzzy Sets and Systems, 147 (2004), 385-403
##[5]
B. Bede, S. G. Gal, Generalizations of the differentiability of fuzzy-number-valued functions with applications to fuzzy differential Equations, Fuzzy Sets and Systems, 151 (2005), 581-99
##[6]
Y. Chalco-Cano, H. Roman-Flores, On new solutions of fuzzy differential equations, Chaos Solitons Fractals, 38 (2008), 112-119
##[7]
Y. Chalco-Cano, H. Roman-Flores, Comparation between some approaches to solve fuzzy differential equations, Fuzzy Sets and Systems, 160 (2009), 1517-1527
##[8]
Y. Chalco-Cano, H. Roman-Flores, M. A. Rojas-Medar, Fuzzy differential equation with generalized derivative, 2008 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2008), New York (2008)
##[9]
Y. J. Cho, H. Y. Lan, The existence of solution for the nonlinear first order fuzzy differential equations with iscontinuous conditions, Dynamics Continuous Discrete Inpulsive Systems Ser. A, 14 (2007), 873-884
##[10]
P. Diamond, Brief note on the variation of constants formula for fuzzy differential equations, Fuzzy Sets and Systems, 129 (2002), 65-71
##[11]
O. Kaleva , Fuzzy differential equations, Fuzzy Sets and Systems, 24 (1987), 301-317
##[12]
O. Kaleva , A note on fuzzy differential equations, Nonlinear Analysis, 64 (2006), 895-900
##[13]
V. lakshmikantham, R. N. Mohapatra, Theory of fuzzy differential equation and inclusions, CRC press, London (2003)
##[14]
J. J. Niteo, R. Rodriguez-Lopez, D. Franco, Linear first-order fuzzy differential equation, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 14 (2006), 687-709
##[15]
S. Abbasbandy, T. A. Viranloo, O. Lopez-Pouso, J. J. Niteo, Numerical Methods for Fuzzy Differential Inclusions, Computers and Mathematics with Applications, 48 (2004), 1633-1641
##[16]
J. J. Buckley, T. Feuring, Fuzzy differential equations, Fuzzy Sets and Systems, 110 (2000), 43-54
##[17]
S. Abbasbandy, J. J. Nieto, M. Alavi, Tuning of reachable set in one dimensional fuzzy differential inclusions, Chaos Solitons Fractals, 26 (2005), 1337-1341
]
Application of Adomian Decomposition Method for Solving Impulsive Differential Equations
Application of Adomian Decomposition Method for Solving Impulsive Differential Equations
en
en
In this work, we apply the Adomian Decomposition Method(ADM) for solving first
order impulsive differential equations
\[x(t)=\alpha x, t\neq k, t>0,\]
\[\Delta x=\beta x, t=k,\]
\[x(0^+)=x_0,\]
where \(\alpha\neq 0,\beta, x_0\in R, 1+\beta\neq 0, k\in N\) are investigated. We compare this method
with others numerical methods such as \(\theta\)-method, Runge-kutta method for
solving impulsive differential equations.
672
681
H.
Hossainzadeh
G. A.
Afrouzi
A.
Yazdani
Impulsive differential equations
Adomian Decomposition Method
\(\theta\)-method
Runge-Kutta method.
Article.12.pdf
[
[1]
D. D. Bainov, A. Dishliev, Population dynamics control in regard to minimizing the time necessary for the regeneration of a biomass taken away from the population, Comptes rendus de l’Academie Bulgare des Sciences, 42 (1989), 29-32
##[2]
D. D. Bainov, P. S. Simenov, Systems with Impulse Effect Stability Theory and Applications, Ellis Horwood Limited, Chichester (1989)
##[3]
A. Dishliev, D. D. Bainov, Dependence upon initial conditions and parameters of solutions of impulsive differential equations with variable structure, International Journal of Theoretical Physics, 29 (1990), 655-676
##[4]
V. D. Mil’man, A. D. Myshkis, On the stability of motion in the presence of impulses, Sib. Math. J., 1 (1960), 233-237
##[5]
M. U. Akhmet, On the general problem of stability for impulsive differential equations, J. Math. Anal. Appl., 288 (2003), 182-196
##[6]
D. D. Bainov, P. S. Simeonov, Systems with impulse effect: stability, theory and applications, Ellis Horwood Limited, Chichester (1989)
##[7]
L. Z. Dong, L. Chen, L. H. Sun, Extiction and permanence of the predator-prey system with stocking of prey and harvesting of predator impulsively, Math. Meth. Appl. Sci., 29 (2006), 415-425
##[8]
V. Lakshmikantham, D. D. Bainov, P. S. Simeonov, Theory of Impulsive Differential Equations, World Scientific, Singapore (1989)
##[9]
A. M. Samoilenko, N. A. Perestyuk, Impulsive Differential Equations, World Scientific, Singapore (1995)
##[10]
G. Kulev, D. D. Bainov, On the stability of systems with impulsive by sirect method of Lyapunov, J. Math. Anal. Appl., 140 (1989), 324-340
##[11]
D. D. Bainov, G. Kulev, Application of Lyapunov’s functions to the investigation of global stability of solutions of system with impulses, Appl. Anal., 26 (1988), 255-270
##[12]
B. M. Randelovic, L. V. Stefanovic, B. M. Dankovic, Numerical solution of impulsive differential equations, Facta Univ. Ser. Math. Inform., 15 (2000), 101-111
##[13]
X. J. Ran, M. Z. Liu, Q. Y. Zhu, Numerical methods for impulsive differential equation, Mathematical and computer modelling, 48 (2008), 46-55
##[14]
X. L. Fu, B. Q. Yan, Introduction to the Impulsive Differential System, Scientific Publishers, 2005 (2005), 1-33
##[15]
Y. Cherruault, Modèles et Méthodes Mathématiques pour les Sciences du Vivant, Presses Universitaires de France, Paris (1998)
##[16]
Y. Cherruault, G. Adomian, Decomposition methods: a new proof of convergence, Math. Comput. Model., 18 (1993), 103-106
##[17]
K. Abbaoui, Y. Cherruault, Convergence of Adomian’s method applied to differential equations, Comput. Math. Appl., 28 (1994), 103-109
]
Hahn-banach Theorem for Functionals on Hypervector Spaces
Hahn-banach Theorem for Functionals on Hypervector Spaces
en
en
In this paper we prove Hahn-Banach Theorem for functionals on hypervector spaces. In this regard, we introduce a new category of hypervector spaces and prove some results for them.
682
690
Ali
Taghavi
Roja
Hosseinzadeh
hypervector space
normed hypervector space
functional.
Article.13.pdf
[
[1]
R. Ameri, Fuzzy hypervector spaces over valued fields, Iranian Journal of Fuzzy Systems, 2 (2005), 37-47
##[2]
P. Corsini, A new connection between hypergroups and fuzzy sets, Southeast Asian Bulletin of Mathematics, 27 (2003), 221-229
##[3]
P. Corsini, Prolegomena of hypergroup theory, Aviani editore, Italy (1993)
##[4]
P. Corsini, V. Leoreanu, Applications of Hyperstructure theory, Kluwer Academic Publishers, Dordrecht (2003)
##[5]
V. Leoreanu, Direct limits and inverse limits of SHR semigroups, Southeast Asian Bulletin of Mathematics, 25 (2001), 421-426
##[6]
V. Leoreanu Fotea, L. Leoreanu, About a sequence of hyperstructures associated with a rough set, Southeast Asian Bulletin of Mathematics, Vol. 34, 113--119 (2010)
##[7]
F. Marty, Sur une generalization de la notion de group, 8𝑡h Congress of the Scandinavian Mathematics (Stockholm), 1934 (1934), 45-49
##[8]
S. Pianskool, W. Hemakul, S. Chaopraknoi, On Homomorphisms of Some Multiplicative Hyperrings, Southeast Asian Bulletin of Mathematics, 32 (2008), 951-958
##[9]
A. Taghavi, R. Hosseinzadeh, A note on dimension of weak hypervector spaces, Italian J. Pure Appl. Math., 33 (2014), 7-14
##[10]
A. Taghavi, R. Hosseinzadeh, Operators on normed hypervector spaces, Southeast Asian Bulletin of Mathematics, 35 (2011), 367-372
##[11]
A. Taghavi, R. Parvinianzadeh, Hyperalgebras and Quotient Hyperalgebras, Italian J. Pure Appl. Math., 26 (2009), 17-24
##[12]
M. Scafati-Tallini, Characterization of remarkable Hypervector space, Proc. 8th congress on Algebraic Hyperstructures and Aplications (Samotraki, Greece), 2002 (2002), 231-237
##[13]
M. Scafati-Tallini, Weak Hypervector space and norms in such spaces, Algebraic Hyperstructures and Applications, 1994 (1994), 199-206
##[14]
T. Vougiouklis, The fundamental relation in hyperrings, In: The general hyperfield: Algebraic hyperstructures and applications, 1991 (1991), 203-211
##[15]
T. Vougiouklis, Hyperstructures and their representations, Hadronic Press, Palm Harber (1994)
]
The Generalized Power Series Distributions and Their Application
The Generalized Power Series Distributions and Their Application
en
en
Necessity of the use of more rich family discrete distributions is practically observable. In this paper, we study about new family of discrete distributions, as Inflated Parameter distributions. Then , we use the application of these distributions for data modeling of Insurance claims and indicate that these distributions have more appropriate approximation then corresponding distributions.
691
697
Fereshteh
Momeni
Generalized Power Series Distribution
zero-Inflated distribution.
Article.14.pdf
[
[1]
N. L. Johnson, A. W. Kemp, S. Kotz, Univariate Discrete Distributions, John Wiley & Sons, U.S.A. (1992)
##[2]
L. D. Minkova, A Generalization of the Classical Discrete Distributions, Communications in Statistics-Theory and Methods, 31 (2002), 871-888
##[3]
N. Kolev, L. Minkova, P. Neytchev, Inflated – Parameter Family of Generalized Power Series Distributions and their applications in Analysis of Overdispesed Insurance Data, ARCH, 26 pages (2000)
##[4]
P. L. Gupta, R. C. Gupta, R. C. Tripathi, Inflatrd Modified Power Series Distributions with applications, Communications in Statistics-Theory and Methods, 24 (1995), 2355-2374
##[5]
N. L. Bowers, H. U. Gerber, J. C. Hickman, D. A. Jones, C. J. Nesbitt, Actuarial Mathematics, Society of Actuaries, New York (1997)
##[6]
T. Rolski, H. Schmidli, V. Schmidt, J. L. Teugels, Stochastic Processes for Insurance and Finance, John Wiley & Sons, Chichester (1999)
##[7]
R. Winkelmann, Econometric Analysis of Count Data, Springer-Verlag, Berlin (2000)
]
A Note on Compact Operators Via Orthogonality
A Note on Compact Operators Via Orthogonality
en
en
In this paper, we extend the usual notion of orthogonality to Banach spaces. Also,
we establish a characterization of compact operators on Banach spaces that admit
orthonormal Schauder bases.
698
701
Hossein
Asnaashari Eivary
Orthogonality
compact operator.
Article.15.pdf
[
[1]
G. Birkhoff, Orthogonality in linear metric spaces, Duke Math. J., 1 (1935), 169-172
##[2]
J. B. Conway, A course in functional analysis, Springer-Verlag, New York (1985)
##[3]
F. Hirsch, G. Lacombe, Elements of functional analysis, Springer-Verlag, New York (1999)
##[4]
R. C. James, Orthogonality in normed linear spaces, Duke Math. J., 12 (1945), 291-302
##[5]
B. D. Roberts, On the geometry of abstract vector spaces, Tohoku Math. J., 39 (1934), 42-59
##[6]
F. B. Saidi, An extension of the notion of orthogonality to Banach Spaces, Journal of mathematical analysis and applications, 267 (2002), 29-47
##[7]
I. Singer, Unghiuri abstracte si functii trigonometrice n spatii Banach, Buletin Stiintific, Sectia de Stiinte Matematice si Fizice, 9 (1957), 29-42
]
On Fuzzy Homomorphisms Between Hypernear-rings
On Fuzzy Homomorphisms Between Hypernear-rings
en
en
We focus on the study of the structure of hypernear-rings,in this paper,we
recall the basics of crisp homomorphism between hyperstructures,particularly,between
hypernear-rings and, then,the notion of fuzzy homomorphism between hypernearrings
is established and its main properties are analysed.
702
716
E.
Hendukolaii
Hypernear-rings
fuzzy homomorphisms
fuzzy ideals
fuzzy congruences.
Article.16.pdf
[
[1]
R. Ameri, E. Hendoukolaii, Fuzzy Hypernear-rings, Ital. J. Pure Appl. Math., (to appear)
##[2]
R. Belohlavek, Determinism and fuzzy automata, Inform. Sci., 143 (2002), 205-209
##[3]
M. Benado, Les ensembles partiellement ordonnes et Le theorem derafinement de Schreier, Czechoslovak Mathematical Journal, 5 (1955), 308-344
##[4]
I. P. Cabrera, P. Cordero, G. Gutierrez, J. Martinez, M. Ojeda- Aciego, Fuzzy congruence relations on nd-groupoids, International Journal of Computer Mathematics, 86 (2009), 1684-1695
##[5]
I. P. Cabrera, P. Cordero, G. Gutierrez, J. Martinez, M. Ojeda- Aciego, Congruence relations on some hyperstructures, Annals Math. Artif. Intell., Vol. 56, 361--370 (2009)
##[6]
I. P. Cabrera, P. Cordero, G. Gutierrez, J. Martinez, M. Ojeda-Aciego, On fuzzy homomorphism between hyperrings, Spanish Science Ministry, Spain (2010)
##[7]
M. Ciric, J. Ignjatovic, S. Bogdanovic, Uniform Fuzzy relations and fuzzy functions, Fuzzy Sets and Systems, 160 (2009), 1054-1081
##[8]
P. Corsini , A new connection between hypergroups and fuzzy sets, Southeast Asian Bull. Math., 27 (2003), 221-229
##[9]
V. Dasic, Hypernear-rings, Proc. Fourth Int. Congress on Algebraic Hyperstructures and Applications (AHA 1990), 1991 (1991), 75-85
##[10]
B. Davvaz, Some results on congruences on semihypergroups, Bulletin of the Malaysian Mathematical Sciences Society, 23 (2000), 53-58
##[11]
B. Davvaz, Isomorphism theorems of hyperrings, Indian J. Pure Appl. Math., 35 (2004), 321-331
##[12]
M. Demirci, Fuzzy functions and their applications, J. Math. Anal. Appl., 252 (2000), 495-517
##[13]
M. Demirci, Gradation of being fuzzy function, Fuzzy Sets and Systems, 119 (2001), 383-392
##[14]
M. Demirci, Constructions of fuzzy functions based on fuzzy equalities, Soft Computing, 7 (2003), 199-207
##[15]
V. M. Gontineac, On hypernear-rings and H-hypergroups, Proc. Fifth Int. Congress on Algebraic Hyperstructures and Applications (AHA 1993), 1994 (1994), 171-179
##[16]
F. Klawonn, Fuzzy points, fuzzy relations and fuzzy function, in: Discovering the World with Fuzzy Logic, 2000 (2000), 431-453
##[17]
M. Krasner, A class of hyperrings and hyperfields, International Journal of Mathematics and Mathematical Sciences, 6 (1983), 307-311
##[18]
F. Marty, Sur une généralisation de la notion de group, 8th Congress Math. Scandinaves (Stockholm), 1934 (1934), 45-49
##[19]
J. Medina, M. Ojeda-Aciegoand, J. Ruiz-Calvino, Fuzzy logic programming via multilattices, Fuzzy Sets and Systems, 6 (2007), 674-688
##[20]
T. Petkovic, Congruences and homomorphisms of Fuzzy automata, Fuzzy Sets and Systems, 157 (2006), 444-458
##[21]
T. Vougiouklis, Hyperstructures and Their Representations, Hadronic Press, Palm Harber (1994)
##[22]
L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353
##[23]
J. Zhan, B. Davvaz, K. P. Shum, A new view of Fuzzy hypernear-rings, Inform. Sci., 178 (2008), 425-438
]
Some New Smooth Fuzzy Relational Compositions
Some New Smooth Fuzzy Relational Compositions
en
en
Fuzzy relational compositions (FRCs) are the core of the fuzzy relational models (FRMs) which play a significant role in the fuzzy linguistic modeling. In this paper, we introduce some new fuzzy relational compositions. These FRCs are composed of some new t-norms and t-conorms and have some good properties such as differentiability. In this regard, the properties of the proposed t-norms and t-conorms are studied and compared with the other ones. Finally, as the most important applications of the FRCs suggest that the new FRCs are to be used in fuzzy relational modeling of some benchmark problems to justify their usage. We show by simulations that the proposed FRCs yield fuzzy relational dynamic systems with very good modeling capabilities.
717
722
Arya
Aghili Ashtiani
Mohammad Bagher
Menhaj
Differential/Smooth fuzzy relational composition
FRC
list of fuzzy t-norms and t-conorms
n-D-to-one mapping
fuzzy relational modeling.
Article.17.pdf
[
[1]
W. Pedrycz, An identification algorithm in fuzzy relational systems, Fuzzy Sets and Systems, 13 (1984), 153-167
##[2]
A. Aghili Ashtiani, M. B. Menhaj, Numerical solution of fuzzy relational equations based on smooth fuzzy norms, Soft Computing, 14 (2010), 545-557
##[3]
M. C. Mackey, L. Glass, Oscillation and chaos in a physiological control system, Science, 297 (1977), 197-287
##[4]
A. E. Gaweda, J. M. Zurada, Data-driven linguistic modeling using relational fuzzy rules, IEEE transactions on fuzzy systems, 11 (2003), 121-134
]