]>
2012
5
2
70
Optimization of Nonlinear Optical Rectification Coefficient in Asymmetric Double Quantum Wells
Optimization of Nonlinear Optical Rectification Coefficient in Asymmetric Double Quantum Wells
en
en
In this work, the particle swarm optimization is used as an optimization optical rectification
coefficient for square double quantum wells. By combining this algorithm together with numerical
solution of Schrödinger equation, and using the density-matrix method we found the wells
structure that the optical rectification coefficient is maximum.
Application of this algorithm to the structure of asymmetric double quantum wells shows
that the optical rectification coefficient is \(6.82\times 10^{-14}\)V/ m .
75
81
Naser
Zamani
Alireza
Keshavarz
Mohammad
Soliemanivareki
Particle Swarm Optimization
Optical Rectification Coefficient
Asymmetric Double Quantum Wells.
Article.1.pdf
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G. Rezaei, M. J. Karimi, A. Keshavarz, Excitonic effects on the nonlinear intersubband optical properties of a semi-parabolic one-dimensional quantum dot, Physica E, 43 (2010), 475-481
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J. Kennedy, The particle swarm: social adaptation of knowledge, IEEE Int. Conf. Evol, Comput (1997)
]
Union and Intersection Fuzzy Subhypergroups
Union and Intersection Fuzzy Subhypergroups
en
en
In this paper, some properties of union and intersection fuzzy subhypergroups are discussed.
Generally, intersection family of fuzzy subhypergroups of a hypergroup is fuzzy subhypergroup,
but, union family of fuzzy subhypergroups of a hypergroup is not fuzzy subhypergroup. We give
some conditions such that this family is fuzzy subhypergroup.
82
90
Esmail
Ranjbar-Yanehsari
Mohsen
Asghari-Larimi
Hyperstructure
Fuzzy sets
Fuzzy subhypergroup.
Article.2.pdf
[
[1]
M. Asghari-Larimi, B. Davvaz, Hyperstructures associated to arithmetic functions, ArsCombitoria, 97 (2010), 51-63
##[2]
M. Asghari-Larimi, V. Leoreanu-Fotea, A connection between hypergroupoids and L-Fuzzy Sets of Type 2, Italian J. of Pure and Appl. Math., 26 (2009), 207-216
##[3]
P. Corsini, A new connection between hypergroups and fuzzy sets, Southeast, Asian Bull.Math. , 27 (2003), 221-229
##[4]
P. Corsini, Prolegomena of hypergroup theory, Second edition, Aviani editor (1993)
##[5]
P. Corsini , Join spaces, power sets, fuzzy sets, Algebraic hyperstructures and applications (Iasi, 1993), 45-52, Hadronic Press, Palm Harbor, FL (1994)
##[6]
P. Corsini, V. Leoreanu-Fotea, Applications of hyperstructure theory, Advances in Mathematics, Kluwer Academic Publishers, Dordrecht (2003)
##[7]
B. Davvaz, V. Leoreanu-Fotea, Hyperring theory and Applications, Hadronic Press, Inc,115, Palm Harber, USA (2009)
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F. Marty, Sur une generalization de la notion de groupe, 8th Congress Math. Scandenaves,Stockholm, (1934), 45-49
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J. N. Mordeson, K. R. Bhutani, A. Rosenfeld, Fuzzy Group Theory, World Scientific, Singapore (2005)
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T. K. Mukherjee, M. K. Sen, On fuzzy ideals of a ring (1), Fuzzy Sets and Systems, 21 (1987), 99-104
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A. Rosenfield, Fuzzy groups, J. Math. Appl. , 35 (1971), 512-517
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T. Vougiouklis, Hyperstructures and their representations, Hadronic Press, Inc, 115, PalmHarber, USA (1994)
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L. A. Zadeh, Fuzzy Sets, Inform and Control , 8 (1965), 338-353
]
A Genetic Algorithm for Solving Scheduling Problem
A Genetic Algorithm for Solving Scheduling Problem
en
en
This paper considers a single machine family scheduling problem where jobs are partitioned into
families and setup is required between these families. The objective is to find an optimal schedule
that minimizes the total weighted completion time of the given jobs in the presence of the sequence
independent family setup times. This problem has been proven to be strongly NP-hard. We
introduce a genetic algorithm that employs an innovative crossover operator that utilizes an
undirected bipartite graph to find the best offspring solution among an exponentially large number
of potential offspring. Computational results are presented. The proposed algorithm is shown to be
superior when compared with other local search methods namely the dynamic length tabu search
and randomized steepest descent method.
91
96
Habibeh
Nazif
genetic algorithm
single machine scheduling
completion time.
Article.3.pdf
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H. A. J. Crauwels, A. M. A. Hariri, C. N. Potts, L. N. Van Wassenhove, Branch and bound algorithm for single machine scheduling with batch set-up times to minimize total weighted completion time, Annals of Operations Research, 83 (1998), 59-76
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]
Efficient Analytical Approaches for Motion of a Spherical Solid Particle in Plane Couette Fluid Flow Using Nonlinear Methods
Efficient Analytical Approaches for Motion of a Spherical Solid Particle in Plane Couette Fluid Flow Using Nonlinear Methods
en
en
In this study, we approach a spherical particle in plane Couette fluid flow problem utilizing
Adomian’s decomposition method (ADM) as well as variational iteration method (VIM) to find a
rapidly convergent power series solution. Equation of particle’s motion in Couette flow considering
the rotation and shear effects on lift force and neglecting gravity has been investigated by Vander
Werff. The required time and distance for a spherical particle to reach terminal velocity trajectory
of particle obtained which has application in transferring the medicine in blood in medical area or
control of particles motion during spraying or injecting processes in industry. The precious
contribution of the work is introducing a new fast and efficient solution of analytical methods in a
spherical particle in plane Couette fluid flow over the previous numerical and analytical
counterpart results in literature, while it is shown that both methods give approximations of a high
degree of accuracy and least computational effort for studying particle motion in Couette fluid flow.
97
104
S. E.
Ghasemi
S. Jalili
Palandi
M.
Hatami
D. D.
Ganji
Spherical particle
Couette flow
Adomian’s decomposition method
variational iteration method.
Article.4.pdf
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[1]
M. Jalaal, M. G. Nejad, P. Jalili, M. Esmaeilpour, H. Bararnia, E. Ghasemi, S. Soleimani, D. D. Ganji, S. M. Moghimi, Homotopy perturbation method for motion of a spherical solid particle in plane Couette fluid flow, Comput. And Math. With Appl., 61 (2011), 2267-2270
##[2]
D. Jan, J. C. Chen, Movements of a sphere rolling down an inclined plane, J.Hydraulic Res., 35 (5) (1997), 689-706
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H. N. Yow, M. J. Pitt, A. D. Salman, Drag correlations for particles of regular shape, Advanced Powder Technol., 16(4) (2005), 363-372
##[4]
M. Jalaal, D. D. Ganji, On unsteady rolling motion of spheres in inclined tubes filled with incompressible Newtonian fluids, Advanced Powder Technol., 22 (2011), 58-67
##[5]
M. Jalaal, D. D. Ganji, An analytical study on motion of a sphere rolling down an inclined plane submerged in a Newtonian fluid, Powder Technol., 198 (2010), 82-92
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]
Bco-based Optimized Heuristic Strategies for Qos Routing
Bco-based Optimized Heuristic Strategies for Qos Routing
en
en
Obtaining an optimized rout such that satisfies Quality factors of Service is a main problem in
scope of optimum routings. The search of route that satisfies such multi-constraints as delay, jitter,
cost and bandwidth in network can facilitate the solution to multi-media transmission. In this
paper, we present a new intelligent routing algorithm QOS using swarm intelligence strategy of bee
colony. Swarm intelligence is a relatively novel field. It addresses the study of the collective
behaviors of systems made by many components that coordinate using decentralized controls and
self-organization. In order to evaluate our strategy, simulation performed under coverage of one of
current services of multimedia applications, Video Conference by means of Powerful Simulator of
OPNET. Then by MATLAB software, we compared efficiency function of proposed method based on
honey bee with genetic algorithm, other current heuristics in QOS. So the strength and accuracy of
our method using performed simulations is clear.
105
114
Arash Ghorbannia
Delavar
Somayyeh
Hoseyny
Rouhollah
Maghsoudi
Swarm Intelligence
Bee Colony Optimization
QOS Routing.
Article.5.pdf
[
[1]
Ping Chen, Tian-lin Dong, A fuzzy genetic algorithm for QoS multicast routing, Computer Communications , 26 (2003), 506-512
##[2]
A. T. Haghighat, K. Faez, M. Dehghan, A. Mowlaei, Y. Ghahremani, GA-Based Heuristic Algorithms for QoS Based Multicast Routing, Knowledge-Based Systems , 16 (2003), 305-312
##[3]
Jun Huang, Yanbing Liu, MOEAQ: A QoS-Aware Multicast Routing algorithm for MANET, Expert Systems with Applications , 37 (2010), 1391-1399
##[4]
Xingwei Wang, Jiannong Cao, Hui Cheng, Min Huang, QoS multicast routing for multimedia group communications using intelligent computational methods, Computer Communications , 29 (2006), 2217-2229
##[5]
F. Xiang, L. Junzhou, W. Jieyi, G. Guanqun, QoS routing based on genetic algorithm, Computer Communications, 22 (1999), 1392-1399
##[6]
Hua Wang, Zhao Shi, Anfeng Ge, Chaoying Yu, An optimized ant colony algorithm based on the gradual changing orientation factor for multi-constraint QoS routing , Computer Communications , 32 (2009), 586-593
##[7]
Muhammad Saleem, Gianni A. Di Caro, Muddassar Farooq, Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions, Information Sciences , (2010), -
##[8]
G. A. Di Caro, Ant Colony Optimization and Its Application to Adaptive Routing in Telecommunication Networks, Ph.D. Thesis, Faculté des Sciences Appliquées, Université Libre de Bruxelles (ULB), Brussels, Belgium (2004)
##[9]
G. A. Di Caro, F. Ducatelle, L. Gambardella, AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks, European Transactions on Telecommunications (ETT) (Special Issue on Self Organization in Mobile Networking)., 16 (2) (2005), 443-455
##[10]
G. A. Di Caro, F. Ducatelle, L. Gambardella, Theory and practice of Ant Colony Optimization for routing in dynamic telecommunications networks, in: N. Sala, F. Orsucci (Eds.), Reflecting Interfaces: The Complex Coevolution of Information Technology Ecosystems, Idea Group, Hershey, PA, USA, (2008), 11-32
##[11]
R. Ghasemaghaei, M. A. Rahman, W. Gueaieb, A. El Saddik, Ant colony-based reinforcement learning algorithm for routing in wireless sensor networks, in: Proceedings of the IEEE Instrumentation and Measurement Technology Conference (IMTC), (2007), 2173-2178
##[12]
K. M. Sim, W. H. Sun, Ant colony optimization for routing and load balancing: survey and new directions, IEEE Transactions on System, Man and Cybernetics2003) , 33 (5) (2003), 560-572
##[13]
Yannis Marinakis, Magdalene Marinaki, Georgios Dounias, Honey bees mating optimization algorithm for the Euclidean traveling salesman problem, Information Sciences, (2010), -
##[14]
M. Farooq, G. A. Di Caro, Routing protocols inspired by insect societies, in: C. Blum, D. Merkle (Eds.), Swarm Intelligence, Introduction and Applications, Natural Computing Series, Springer-Verlag, (2008), 101-160
##[15]
M. Saleem, M. Farooq, Beesensor: a bee-inspired power aware routing protocol for wireless sensor networks, in: Proceedings of the 4th EvoCOMNET Workshop, LNCS, vol. 4448 (2007)
##[16]
Smart L. Sabat, Siba K. Udgata, Ajith Abraham, Artificial bee colony algorithm for small signal model parameter extraction of MESFET, Engineering Application of Artificial Intelligence, 23 (5) (2010), 689-694
##[17]
Dervis Karaboga, Bahriye Akay, A Comparative Study of Artificial Bee Colony Algorithm, Applied Mathematics and Computation, 214 (2009), 108-132
##[18]
Shyam Sundar, Alok Singh, A Swarm Intelligence Approach to the Quadratic Minimum Spanning Tree Problem, Information sciences , 180 (2010), 3182-3191
##[19]
Bahriye Akay, Dervis Karaboga, A Modified Artificial Bee Colony Algorithm for Real-parameter Optimization, Information Sciences, Available online 27 July 2010. (2010)
##[20]
Li-Pei Wong, Chin Soon Chong, An Efficient Bee Colony Optimization Algorithm for Traveling Salesman Problem using Frequency-based Pruning, 7th IEEE International Conference on Industrial Informatics , (2009)
]
Intuitionistic Fuzzy Sets and Join Spaces Associated with Ary Membership Functions
Intuitionistic Fuzzy Sets and Join Spaces Associated with Ary Membership Functions
en
en
In this paper, we associate finite hyperstructures with fuzzy sets endowed with n-ary
membership functions and analyze the properties of this new hyperstructures. We prove that the
new hyperstructure is a commutative hypergroup, but generally it is not a join space. We give some
conditions such that the hypergroup has this property. In particular, we investigate some natural
equivalence relations on the set of all intuitionistic fuzzy sub-hypergroups of a hypergroup.
115
125
Mohsen
Asghari-Larimi
Piergiulio
Corsini
Esmail
Ranjbar-yanehsari
Hyperstructure
Join space
Fuzzy subhypergroup
Intuitionistic fuzzy subhypergroups.
Article.6.pdf
[
[1]
M. Asghari-Larimi , Some properties of intuitionistic nil radicals of intuitionistic fuzzy ideals, International Mathematical Forum, 5 (2010), 1551-1558
##[2]
M. Asghari-Larimi, B. Davvaz, Hyperstructures associated to arithmetic functions, Ars Combitoria, 97 (2010), 51-63
##[3]
M. Asghari-Larimi, V. Leoreanu-Fotea, A connection between hypergroupoids and L-Fuzzy Sets of Type 2, Italian J. of Pure and Appl. Math., 26 (2009), 207-216
##[4]
K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets Syst, 20 (1986), 87-96
##[5]
K. T. Atanassov, New operations defined over the intuitionistic fuzzy sets, Fuzzy Sets Syst., 61 (1994), 137-142
##[6]
R. Biswas, Intuitionistic fuzzy subgroups, Math. Forum, 10 (1989), 37-46
##[7]
P. Corsini, Prolegomena of Hypergroup Theory, Aviani Editore, (1993)
##[8]
P. Corsini, Join Spaces, Power Sets, Fuzzy Sets, Proceedings of the 5th A.H.A. Congress, 1993, Iasi (Romania) Hadronic Press, (1994), 45-52
##[9]
P. Corsini, Hyperstructures associated with ordered sets, Bull. Greek Math. Soc., 48 (2003), 7-18
##[10]
P. Corsini, Hyperstructures associated with fuzzy sets endowed with two membership functions, j. of combin. infor. system sci., 1-4 (2006), 247-254
##[11]
P. Corsini, A new connection between hypergroups and fuzzy sets, Southeast Asian Bull. Math., 27 (2003), 221-229
##[12]
P. Corsini, V. Leoreanu-Fotea, Applications of Hyperstructure Theory, Kluwer Academic Publications, Dordrecht, Advances in Mathematics (2003)
##[13]
I. Cristea, Hyperstructures and fuzzy sets endowed with two membership functions, Fuzzy sets and Systems, 160 (2009), 1114-1124
##[14]
W. A. Dudek, B. Davvaz, Y. B. Jun, On intuitionistic fuzzy sub-quasihypergroups of quasihypergroups, Information Sciences, 170 (2005), 251-262
##[15]
F. Marty, Sur une generalisation de la notion de groupe, 8th course Math. Scandinaves Stockholm, (1934), 45-49
##[16]
W. Prenowitz, Projectives Geometries as Multigroups , Amer. J. Math., 65 (1943), 235-256
##[17]
W. Prenowitz, J. Jantosciak, Join geometries , Springer-Verlag, UTM (1979)
##[18]
T. Vougiouklis , Hyperstructures and their representations, Hadronic Press, Inc, 115, PalmHarber, USA (1994)
##[19]
L. A. Zadeh, Fuzzy Sets, Inform and Control, 8 (1965), 338-353
]
Intelligent Control System of Automobile Window Using Fuzzy Logic
Intelligent Control System of Automobile Window Using Fuzzy Logic
en
en
It has been attempted to develop an intelligent control system based on fuzzy logic to regulate height of
automobile windows in this paper. An ATMega32 microcontroller is responsible for the system of fuzzy
control programmed by Bascom AVR software. The control system involves two manual and automatic
modes. In the automatic mode, there is no need to keep switch pressed for complete up and down functions
of the window. Meanwhile, using the designed system is both convenient and accurate with the possibility
to regulate position of the window after turning off the car. Another feature of this system is its sensitivity
to carbon monoxide and carbon dioxide gasses. Whenever the extent of \(CO\) or \(CO_2\) gasses exceeds an
allowable limit, the windows will automatically come down in order to prevent asphyxiation of passengers.
Simulation was implemented by MATLAB using fuzzy logic and the obtained results were compared with
those from fuzzy linear regression method.
126
133
Seyyed Kamaloddin Mousavi
Mashhadi
Amir
Aminian
Mojtaba Shokohi
Nia
regulating height of automobile window
sensitivity to \(CO\) and \(CO_2\)
fuzzy linear regression
MATLAB fuzzy logic.
Article.7.pdf
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[1]
George J. Klir Bo Yuan, Fuzzy sets and Fuzzy Logic, Theory and application, prentice Hall PTR. (1995)
##[2]
K. Tanaka, Introduction to Fuzzy Logic for Practical Applications, NY: Springer Press, New-York (1997)
##[3]
C. Kim, K. Seong, H. Kwang, Design and implimentation offegcs: Fuzzy elevator group control system, in1996 Biennial Conf. of the North American Fuzzy Soci., Berkeley,CA, (1996), 1-109
##[4]
E. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, Int. J. Man-Machine Studies, 1 (1975), 1-1
##[5]
S. Chopra, R. Mitra, V. Kumar, Fuzzy controller: Choosing an appropriate and smallest rule set, Int. J. Comp. Cognition, 3 (2005), 1-73
##[6]
G. Nurcahyo, S. Shamsuddin, R. Alias, M. Sap, Selection of defuzzication method to obtain crisp value for representing uncertain data in a modified sweep algorithm, J. Comp. Sci. Tech., 3 (2003), 1-22
]
A Novel Sizing Methodology Based on Match Evaluation Method for Optimal Sizing of Stand-alone Hybrid Energy Systems Using Nsga-ii
A Novel Sizing Methodology Based on Match Evaluation Method for Optimal Sizing of Stand-alone Hybrid Energy Systems Using Nsga-ii
en
en
Wind and solar energy technologies offer clean and renewable energy sources, and are essential
components of sustainable energy future. The current paper presents a new methodology for size
optimization of stand-alone Wind/PV energy systems. The principal objective of this study is to
maximize the electricity match rate between demand and supplies, able to accomplish the energy
requirements of a given load distribution, for a specific site. Mathematical models of hybrid
components are exploited to estimate the total output power using solar radiation, temperature
and wind speed data, collected on the site of Zabol, located in Sistan and Baluchestan, Iran. Then, a
new methodology has been proposed which can obtain the optimal size of each hybrid component.
The objective functions are considered based on supply/demand match evaluation criteria,
minimizing the inequality coefficient (IC) and also maximizing the correlation coefficient (CC),
simultaneously. The elitist non-dominated sorting genetic algorithm (NSGA-II), which is one of the
multi-objective evolutionary algorithm (MOEA), have been employed for a hybrid stand-alone
renewable energy power system (Wind/PV) to find the optimal size of each components. The
Pareto-optimal solution is obtained in order to have higher-level decision. The designers can select
the best configuration among the Pareto set which fits their desire.
134
145
Mohammad Ali Yazdanpanah
Jahromi
Said
Farahat
Seyed Masoud
Barakati
Hybrid Wind/PV systems
multi-objective optimization
sizing method
electricity match rate
Article.8.pdf
[
[1]
Mehdi Vafaei, Optimally-Sized Design of a Wind/Diesel/Fuel Cell Hybrid System fo Remote Community , Master of Applied Science Electrical and Computer , Engineering University of Waterloo (2011)
##[2]
Daming Xu, Longyun Kang, Liuchen Chang, Binggang Cao, Optimal Sizing of Standalone Hybrid Wind/PV Power Systems Using Genetic Algorithms, presented at the IEEE, (2005)
##[3]
Hongxing Yang, Wei Zhou, Lin Lu, Z. Fang, Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm, Solar Energy, ELSEVIER, (2008), 354-367
##[4]
Zhou Wei, Simulation and Optimum Design of Hybrid Solar-Wind and Solar-Wind-Diesel Power Generation Systems, Doctor of Philosophy, The Hong Kong Polytechnic University (2007)
##[5]
D. B. Nelson, M. H. Nehrir, C. Wang, Unit sizing and cost analysis of stand-alone hybrid wind/PV/fuel cell power generation systems, Renewable Energy, ELSEVIER, (2006), 1641-1656
##[6]
Zhou Wei, Yang Hongxing, One Optimal Sizing Method for Designing Hybrid Solar-Wind- Diesel Power generating Systems, presented at the Zhou Wei, Yang Hongxing (2007)
##[7]
D. B. Nelson, M. H. Nehrir, Unit Sizing of Stand-Alone Hybrid Wind/PV/Fuel Cell Power Generation Systems, IEEE, (2005), 1-7
##[8]
B. Ould. Bilala, V. Samboua, C. M. F Kébé, P. A. Ndiaye, M. Ndongo, Methodology to Size an Optimal Stand-Alone PV/wind/diesel/battery System Minimizing the Levelized cost of Energy and the CO2 Emissions, Energy Procedia, ELSEVIER, (2012), 1636-1647
##[9]
R. Luna-Rubio, M. Trejo-Perea, D. Vargas-Vazquez, G. J. Rıos-Moreno, Optimal sizing of renewable hybrids energy systems: A review of methodologies, Solar Energy, ELSEVIER, (2012), 1077-1088
##[10]
Y. S. Zhao, J. Zhan, Y. Zhang, D. P. Wang, B. G. Zou, The Optimal Capacity Configuration of An Indepebdent Wind/PV Hybrid Power Supply System Based on Improved PSOAlgorithm, , (2006)
##[11]
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]