]>
2014
11
3
85
Etdwsn an Method for Energy Efficiency Increase by Combining the Index Parameters in Wireless Sensor Networks
Etdwsn an Method for Energy Efficiency Increase by Combining the Index Parameters in Wireless Sensor Networks
en
en
The development of routing algorithms in wireless sensor networks, energy supply increase in the dependent nodes is by viewing the previous algorithms on the data-centric routing algorithm, the method suggested in ETDWSN we offer combined with the index parameters of the method, we've created suitability function in the ETDWSN method we've reduced energy consumption and also in this case the sensor system network efficiency is increased in The correct using proposals could increase the energy threshold detector on wireless sensor network we have in ETDWSN method with the index parameters select the weight goal we've provided compared with neighboring nodes selection action relative to the source node, we improve the routing space finally The average delay time of the nodes to the Auto GBR،GBR ، GBR-C and have lowered.
166
176
Fatollah
Rouhi
Arash Ghorbannia
Delavar
Sina
Hedayati
Algorithm ETDWSN
Efficiency
FunctionWeigh
Wireless Sensor Network
Distributed Node.
Article.1.pdf
[
[1]
Sina Hedayati, Arash Ghorbannia Delavar , The method of GBR optimization by special parameters to decrease energy onsumption in WSNs , Journal of mathematics and computer science , 8 (2014), 387-397
##[2]
Arash Ghorbannia Delavar, Abootorab Alirezaie, Amir Abbas Baradaran , KGAWSN: An Effective Way to Reduce Energy Consumption in Wireless Sensor Networks by Kmeans and Genetic Algorithms, International Journal of Computer Applications (0975 – 888) , Volume 48– No.12 (2012)
##[3]
V. Shnayder, M. Hempstead, B.-r. Chen, G. W. Allen, M. Welsh, Simulating the power consumption of large-scale sensor network applications, in: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, SenSys ’04, ACM, New York,NY, USA, doi:http://doi.acm.org/10.1145/1031495.1031518., (2004), 188-200
##[4]
T. He, S. Krishnamurthy, J. A. Stankovic, T. Abdelzaher, L. Luo, R. Stoleru, T. Yan, L. Gu, Energy-efficient surveillance system using wireless sensor networks, in: Mobisys, ACM Press, (2004), 270-283
##[5]
G. Tolle, J. Polastre, R. Szewczyk, D. Culler, N. Turner, K. Tu, S. Burgess, T. Dawson, P. Buonadonna, D. Gay. Hong, A macroscope in the redwoods , in: Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, SenSys ’05, ACM, New York,NY, USA, Doi : http ://doi.acm.org /10.1145 /1098918 .1098925. , (2005), 51-63
##[6]
R. K. Ganti, P. Jayachandran, T. F. Abdelzaher, J. A. Stankovic, Satire: asoftware architecture for smart attire , in: Proceedings of the 4th International Conference on Mobile Systems, ,mobiSys’06,ACM,NewYork,NY,USA, doi:http://doi.acm.org/10.1145/1134680.1134693. , (2006), 110-123
##[7]
J. N. Al-Karaki, A. E. Kamal , Routing techniques in wireless sensornetworks: a survey, IEEE Wireless Commun. Mag., doi:10.1109/MWC.2004.1368893. , 11 (6) (2004), 6-28
##[8]
L. Shan-Shan, Z. Pei-Dong, L. Xiang-Ke, C. Wei-Fang, P. Shao-Liang, Energy efficient multipath routing using network coding in wirelesssensor networks, in: T. Kunz, S. Ravi (Eds.), Ad-Hoc, Mobile, andWireless Networks, Springer, Berlin/Heidelberg, 4104 (2006), 114-127
##[9]
Y. S. Y. Yang, C. Zhong, J. Yang, Energy efficient reliable multi-pathrouting using network coding for sensornetwork, IJCSNSInt. J.Comput. Sci. Network Secur, 8(12) (2008), 114-127
##[10]
L. Shan-Shan, Z. Pei-Dong, L. Xiang-Ke, C. Wei-Fang, P. Shao-Liang, Energy efficient multipath routing using network coding in wireless sensor networks, in: T. Kunz, S. Ravi (Eds.), Ad-Hoc, Mobile, and Wireless Networks, Springer,Berlin/Heidelberg, 4104 (2006), 114-127
##[11]
Z. Xiong, W. Liu, J. Huang, W. Cheng, B. Cheng, Network coding approach for intra-cluster information exchange in sensor networks, in: Proc. VTC-2007 Fall Vehicular Technology Conf. 2007 IEEE66th, doi:10.1109/VETECF.2007.49., (2007), 164-168
##[12]
E. Ayday, F. Delgosha, F. Fekri, Location-aware security services for wireless sensor networks using network coding, in: Proc. 26th IEEE Int. Conf. Computer Communications, INFOCOM 2007, IEEE, doi:10.1109/INFCOM.2007.146. , (2007), 1226-1234
##[13]
Z. Zhu, Q. Tan, P. Zhu, Q. Zheng. , Security broadcast based on linear network coding in WSN, in: Proceedings of International Computer Science and Software Engineering Conference, pp. doi:10.1109/CSSE.2008.676., 3 (2008), 919-922
##[14]
T.-G. Li, C.-C. Hsu, C.-F. Chou, On reliable transmission by adaptive network coding in wireless sensor networks, in: ICC ’09. IEEE International Conference on Communications, doi:10.1109/ICC.2009.5199247. , (2009), 1-5
##[15]
Lusheng Miao, Karim Djouani, Anish Kurien, Guillaume Noel Network coding and competitive approach for gradient based routing in wireless sensor networks Ad Hoc Networks, , 10 (2012), 990-1008
]
Wkb and Numerical Compound Matrix Methods for Solving the Problem of Everted Neo-hookean Spherical Shell
Wkb and Numerical Compound Matrix Methods for Solving the Problem of Everted Neo-hookean Spherical Shell
en
en
The present paper deals with an eigenvalue problem which describes an everted neo-hookean spherical shell which its outer surface is deformed in compression under hydrostatic pressure. Our approach is based on mathematical modeling using a differential equation of order four and boundary conditions including two differential equations of order two and three. We solve the above mentioned problem using two different expansions of WKB method. We also investigate how to apply the numerical compound matrix on the problem and show the application of Runge-Kutta-Fehlberg and Newton-Raphson numerical algorithm. Finally, by comparing the data obtained from these two methods (numerical and WKB), we not only learn about the turning point, we also find out that the reason of the difference between the results of the two methods is this turning point.
177
190
Morteza
Sanjaranipour
Hamed
Komeyli
We compound matrix method
elasticity
incompressible
spherical
WKB method
Article.2.pdf
[
[1]
B. S. Ng, W. H. Reid , A Numerical Method for Linear Two-point Boundary-value Problems Using Compound Matrices, Journal of Computational Physics, 30 (1979), 70-85
##[2]
B. S. Ng, W. H. Reid, An Initial Value Matrix Method for Eigen-value Problems Using Compound Matrices , Journal of Computational Physics, 30 (1979), 125-136
##[3]
B. S. Ng, W. H. Reid, The Compound Matrix Method for Ordinary Differential Systems, Journal of Computational Physics, 58 (1985), 209-228
##[4]
Yi-Chao Chen, D. M. Haughton , On the Existence of Elastic Cylinders, Elasticity , 49 (1997), 79-88
##[5]
Y. B. Fu, M. Sanjaranipour , WKB Method with Repeated Roots and its Application to the Buckling Analysis of an Everted Cylindrical Tube, SIAM Journal of Applied Mathematics , 1856–1871 (2002)
##[6]
Y. B. Fu , Some Asymptotic Results Concern the Buckling of Arbitrary Thickness, int. J. Non –linear Mech. , 33 (1978), 1111-1112
##[7]
D. M. Houghton, Yi-Chao Chen , On the Eversion of Incompressible Elastic Spherical Shells, ZAMP , 50 (1999), 312-326
##[8]
D. M. Haughton, Yi-Chao Chen , Asymptotic Bifurcation for the Eversion of Elastic Shells, ZAMP , 54 (2003), 191-211
##[9]
M. Sanjaranipour , WKB Analysis of the Buckling of a Neo-hookean Cylindrical Shell of Arbitrary Thickness Subjected to an External Pressure, International Journal of Applied Mathematics, (2010), 857-870
##[10]
M. Sanjaranipour , Application of WKB Method to Some of the Buckling Problems in Finite Elasticity, Ph. D. thesis Keele, (2001)
##[11]
Y.B. Fu, Y. P. Lin , A WKB Analysis of the Buckling of an Everted Neo-Hookean Cylindrical Tube, Department of Mathematics, Kunming Institute of Science and Technology, Kunming, China (2002)
##[12]
Richard L. Borden, J. Douglas Faires, Albert C. Reynolds, Numerical Analysis, Qoqnoos Publication, Tehran (2000)
##[13]
A. W. Bush , Protection for Engineers and Scientists, School of Computing and Mathematics Teesside, Polytechnic Middleborough, U. k (1992)
##[14]
Alihassan Nyfeh, Introduction to Perturbation Technique, University Distinguished Professor Virginia Polytechnic and University of Blackbury Virginia and Yamourk University Irbid Jordan, (1980)
##[15]
Carl M. Bender, Advanced Mathematical Methods for Scientists and Engineers, copy- right by McGraw-Hill Inc., (1978)
##[16]
P. Chadwick , Continuum Mechanics, Gorge Allen and Unwin, L.td. (1976)
]
Ccgdc: A New Crossover Operator for Genetic Data Clustering
Ccgdc: A New Crossover Operator for Genetic Data Clustering
en
en
Genetic algorithm is an evolutionary algorithm and has been used to solve many problems such as data clustering. Most of genetic data clustering algorithms just have introduced new fitness function to improve the accuracy of algorithm in evaluation of generated chromosomes. Crossover operator is the backbone of the genetic algorithm and should create better offspring and increase the fitness of population with maintaining the genetic diversity. A good crossover should result in feasible offspring chromosomes when we crossover feasible parent chromosomes. In this paper we introduce a new crossover operator for genetic data clustering. Experimental results show that clustered crossover for genetic data clustering (CCGDC) creates better offspring and increases the fitness of population and also will not produce illegal chromosome.
191
208
Gholam Hasan
Mohebpour
Arash Ghorbannia
Delavar
Data mining
data clustering
genetic algorithm
crossover operator
partitioning
Article.3.pdf
[
[1]
John H. Holland, Adaptation in Natural and Artificial Systems, the University of Michigan Press, (1975)
##[2]
Jong De, A. Kenneth , An Analysis of the Behavior of a Class of Genetic Adaptive Systems, Doctoral thesis, Dept. Computer and Communication Sciences, University of Michigan, (1975), -
##[3]
D. E. Goldberg, Genetic Algorithm in Search, Optimization and Machine Learning, Addison –Wesley, New York (1989)
##[4]
L. Davis, Job-shop Scheduling with Genetic Algorithms, Proceedings of an International Conference on Genetic Algorithms and Their Applications, (1985), 136-140
##[5]
I. M. Oliver, D. J. Smith, J. R. C. Holland, A Study of Permutation Crossover Operators on the Travelling Salesman Problem, In J.J. Grefenstette (ed.). Genetic Algorithms and Their Applications: Proceedings of the 2nd International Conference on Genetic Algorithms. Lawrence Erlbaum Associates, Hilladale, NJ ( 1987)
##[6]
S. J. Wu, P. T. Chow, Steady-state genetic algorithm for discrete optimization of trusses, Computers and Structures , 56 (6) (1995), 979-991
##[7]
W. M. Jenkins , On the application of natural algorithms to structural design optimization, Engineering Structure , 19 (4) (1997), 302-308
##[8]
K. Dejong, W. M. Spears, An analysis of the interacting roles of population sizes and crossover in genetic function optimization, in: H.P. Schwefel, R. Manner (Eds.), Proceedings of Parallel Problem Solving from Nature, Springer, Berlin, (1990), 38-47
##[9]
G. Syswerda, Uniform crossover in genetic algorithms, in: J.D. Schaffer, M.Kaufman (Eds.), Proceedings of the Third International Conference on Genetic Algorithms, (1989), 2-9
##[10]
O. Hasancebi, F. Erbatur, Evaluation of crossover operators in genetic algorithms based optimum structural design, Computers and Structures , 78 (2000), 435-448
##[11]
D. Zaharie, Influence of crossover on the behavior of differential evolution algorithms, Applied Soft Computing , 9 (2009), 1126-1138
##[12]
Mustafa Kaya, The effects of two new crossover operators on genetic algorithm performance, Applied Soft Computing, 11 (2011), 881-890
##[13]
Hong He, Yonghong Tan, A two-stage genetic algorithm for automatic clustering, Neurocomputing , 81 (2012), 49-59
##[14]
Dongxia Chang, Yao Zhao, Changwen Zheng, Xianda Zhang, A genetic clustering algorithm using a message-based similarity measure, Expert Systems with Applications , 39 (2012), 2194-2202
##[15]
Amin Aalaei, Hamed Fazlollahtabar, Iraj Mahdavi, Nezam Mahdavi-Amiri, Mohammad Hassan Yahyanejad, A genetic algorithm for a creativity matrix cubic space clustering: A case study in Mazandaran Gas Company, Applied Soft Computing , 13 (2013), 1661-1673
##[16]
Jose A. Castellanos-Garzon, Fernando Diaz, An evolutionary computational model applied to cluster analysis of DNA microarray data, Expert Systems with Applications, 40 (2013), 2575-2591
##[17]
Riccardo Poli, W. B. Langdon, Genetic programming with one-point crossover, In P. K. Chawdhry, R. Roy, and R. K. Pant, editors, Second On-line World Conference on Soft Computing in Engineering Design and Manufacturing. Springer-Verlag London, (1997), 23-27
##[18]
V. A. Cicirello, S. F. Smith, Modeling GA performance for control parameter optimization, In GECCO-2000: Proceedings of the Genetic and Evolutionary Computation Conference, pages 235–242.Morgan Kaufmann Publishers, (2000), 8-12
##[19]
M. Kaya, The effects of two new crossover operators on genetic algorithm performance, Applied Soft Computing, 11(1) (2011), 881-890
##[20]
G. Syswerda, Uniform crossover in genetic algorithms, in: J.D. Schaffer, M.Kaufman (Eds.), Proceedings of the Third International Conference on Genetic Algorithms, (1989), 2-9
##[21]
O. Hasancebi, F. Erbatur, Evaluation of crossover operators in genetic algorithms based optimum structural design, Computers and Structures , 78 (2000), 435-448
##[22]
, , http://repository.seasr.org/Datasets/UCI/arff/, ()
##[23]
R. Maghsoudi , A. Ghorbannia Delavar, S. Hoseyny, R. Asgari, Y. Heidari, Representing the New Model for Improving K-Means Clustering Algorithm based on Genetic Algorithm, The Journal of Mathematics and Computer Science , 2 (2011), 329-336
]
2d Shape Optimization Via Genetic Algorithm
2d Shape Optimization Via Genetic Algorithm
en
en
In this study, among different algorithms that have been introduced for obtaining optimal shapes and
structures, an advanced optimization method for distinct shapes and also non-significant ones is
illustrated. In order to investigate the efficiency of the method, a specific structural member (safety belt)
is analyzed. The optimization process is to optimize the member via genetic algorithm, in order to have
minimum weight; meanwhile having the ability to support the loading and also sustaining the generated
tension stresses under the range of the allowable limit. The main goal of the present work is to focus on
the existence of an optimal shape of the member optimized by genetic algorithm, having necessary
conditions of optimality for a safety belt, and stability of optimal solutions under some prescribed
perturbations.
209
217
Seyed Alireza
Moezi
Ehsan
Zakeri
Yousef
Bazargan-lari
Amin
Zare
Belt
Optimization
Genetic Algorithm
FEM
Shape.
Article.4.pdf
[
[1]
A. Ketabi, M. J. Navardi, Optimization shape of variable-capacitance micromotor using seeker optimized algorithms, journal of electrical engineering and Technology, 7(2) (2012), 212-220
##[2]
S. K. Tiong, D. F. W. Yap, S. P. Koh, A comparative analysis of various chaotic genetic algorithms for multimodal function optimization, Trends Applied Sci. Res., 7 (2012), 785-791
##[3]
A. Ketabi, M. J. Navardi, Optimization Shape of Variable Capacitance Micromotor Using Differential Evolution Algorithm, Mathematical Problems in Engineering, Volume 2010 (2010)
##[4]
B. Baumann, B. Kost, M. Wolff, H. Groninga, T. Blob, S. Knickrehm, Numerical Shape Optimization of Photoacoustic Sample Cells: First Results, Proceedings of the COMSOL Users Conference, October 23-24, Grenoble, France, (2007), 1-6
##[5]
A. Manconi, P. Tizzani, G. Zeni, S. Pepe, G. Solaro, Simulated annealing and genetic algorithm optimization using COMSOL multiphysics: Applications to the analysis of ground deformation in active volcanic areas, Proceedings of the COMSOL Conference, October 14-16, 2009, Milan, Italy, (2009), 1-6
##[6]
J. Shang, L. Zhang, Ant colony algorithm and genetic algorithm optimization for test vector reordering inform, Technol. J., 11 (2012), 1786-1789
##[7]
H. Strandberg, T. Makkonen, J. Leinvuo, Multi-objective optimization of a ball grid array using mode FRONTIER and COMSOL multiphysics, Proceedings of the COMSOL Conference, October 14-16, 2009, Milan, Italy, (2009), 1-7
##[8]
J. H. Holland, Adaptation in Natural and Artificial Systems, 1st Ed., University of Michigan Press, Ann Arbor, Michigan, ISBN: 0472084607 (1975)
##[9]
M. Mashinchi Joubari, M. H. Pashaei, A. Fathi, Sizing optimization of truss structures under Frequency Constraints with Artificial Bee Colony Algorithm, Journal of mathematics and computer Science, 9 (2014), 77-88
##[10]
N. K. Naseri, A Hybrid Cuckoo-Gravitation Algorithm for Cost-optimized QFD Decision-Making Problem, , 9 (2014), 342-351
##[11]
C. B. Cheng, C. J. Cheng, E. S. Lee, Neuro-fuzzy and genetic algorithm in multiple response optimization, Comput. Math. Appl., 44 (2002), 1503-1514
##[12]
W. Pao, X. Chen, L. Chao, Optimization of insulation padding for directional solidification, J. Applied Sci., 13 (2013), 321-325
##[13]
G. R. Liu, Mesh Free Methods: Moving Beyond the Finite Element Method, CRC Press, Boca Raton, FL., ISBN: 9780849312380 (2003)
]
Speech Steganography in Wavelet Domain Using Continuous Genetic Algorithm
Speech Steganography in Wavelet Domain Using Continuous Genetic Algorithm
en
en
In this paper, we present a new adaptive steganography method using Lifting Wavelet Transform
(LWT). In this method, we first calculate the LWT of the sample of host and secret speech signal. Then
wavelet coefficients of secret speech signal will be fitted effectively and efficiently in host signal wavelet
coefficients using continuous genetic algorithm. We used indirect replacement technique in 5 bits host
using a proposed formula. Due to the quantization error, there are some differences between the secret
signal before steganography and the extracted signal after steganography. However, these differences
have an appropriate Gaussian noise model. We compress these differences using Huffman lossless
compression method. The compression rate of such differences approach to the entropy, which is derived
from Shannon's first theorem. Huffman lossless compression method, cause to small noise. We these
compressed differences sent along the stego signal. The experimental results show that the proposed
model has a statistical transparency higher than Least Significant Bit (LSB), Frequency Masking (FM)
and Efficient Wavelet Masking (EWM) algorithms in time domain and frequency domain.
218
230
Hojat Allah
Moghaddasi
Mohammad
Fakhredanesh
Lifting Wavelet Transform (LWT)
Elitism
Incest prevention
Premature convergence
Cycle crossover
Crowding Factor (CF)
Article.5.pdf
[
[1]
D. M. Ballesteros, J. M. Moreno, Highly transparent steganography model of speech signals using Efficient Wavelet Masking, Expert Systems with Applications, 39 (2012), 9141-9149
##[2]
F. Djebbar et al., A view on latest audio steganography techniques, in Innovations in Information Technology (IIT), 2011 International Conference on, (2011), 409-414
##[3]
N. Cvejic, T. Seppanen, A wavelet domain LSB insertion algorithm for high capacity audio steganography, in Digital Signal Processing Workshop, 2002 and the 2nd Signal Processing Education Workshop. Proceedings of 2002 IEEE 10th, (2002), 53-55
##[4]
A. Delforouzi, Mohammad Pooyan, Adaptive digital audio steganography based on integer wavelet transform, Circuits, Systems & Signal Processing , 27 (2008), 247-259
##[5]
T. Manzuri et al., High capacity error free wavelet domain speech steganography, In Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on, (2008), 1729-1732
##[6]
F. Djebbar, H. Hamam, K. Abed-Meraim, D. Guerchi, Controlled distortion for high capacity data-in-speech spectrum steganography, in Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010 Sixth International Conference on, (2010), 212-215
##[7]
D. E. Skopin et al., Advanced algorithms in audio steganography for hiding human speech signal, in Advanced Computer Control (ICACC), 2010 2nd International Conference on, (2010), 29-32
##[8]
J. H. Holland, Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, U Michigan Press, (1975)
##[9]
R. L. Haupt, Optimum population size and mutation rate for a simple real genetic algorithm that optimizes array factors, in Antennas and Propagation Society International Symposium, 2000. IEEE, (2000), 1034-1037
##[10]
D. Whitley, T. Starkweather, D. Shaner, The traveling salesman and sequence scheduling: Quality solutions using genetic edge recombination, Colorado State University, Department of Computer Science (1991)
##[11]
L. J. Eshelman, R. A. Caruana, J. D. Schaffer, Biases in the crossover landscape, in Proceedings of the third international conference on Genetic algorithms, (1989), 10-19
##[12]
Q. Liu, A. H. Sung, M. Qiao, Temporal derivative-based spectrum and mel-cepstrum audio steganalysis, Information Forensics and Security, IEEE Transactions on, 4 (2009), 359-368
##[13]
Y.-C. Qi, L. Ye, C. Liu, Wavelet domain audio steganalysis for multiplicative embedding model, in Wavelet Analysis and Pattern Recognition, ICWAPR 2009. International Conference on, (2009), 429-432
]
Speech Steganography in Wavelet Domain Using Continuous Genetic Numerical Simulation of Cdte Thin Film Solar Cell With Amps-1d
Speech Steganography in Wavelet Domain Using Continuous Genetic Numerical Simulation of Cdte Thin Film Solar Cell With Amps-1d
en
en
We conducted the analysis of parameters and the efficiency of photovoltaic effect in CdTe thin film Solar Cell depending on its thickness variations by use of AMPS-1D software. The simulation of the main parameter has been carried out in order to optimize the performance of thin solar cell. The results are in a good agreement with the result obtained from the literature. In this paper it has been shown, a conversion efficiency of 14.6% has been achieved for 1 μm thick CdTe cell, which indicates that with only 25% CdTe absorber material of the baseline cell the compromise for efficiency is only 0.8% (15.4% to 14.6%).
231
237
A.
Mirkamali
Kh. Kh.
Muminov
K.
Kabodov
AMPS-1D
efficiency
Thickness
thin film
simulation.
Article.6.pdf
[
[1]
W. N. Shafarman, L. Stolt, Handbook of Photovoltaic Science and Engineering , (Wiley Chichester, 2003), chap. Cu (In,Ga)Se2 Solar Cells, (2003), 567-616
##[2]
L. J. Simpson, J. S. Britt, S. Wiedeman, M. E. Beck, B. S. Joshi, T. L. Vincent, J. P. Delplanque, R. J. Kee, N. B. Gomez, K. M. Williams, et al., NCPV and Solar Program Review Meeting , in Proc., (2003), 1-604
##[3]
G. Jensen, J. Schaefer, G. M. Hanket, E. Eser, S. Wiedeman, NCPV and Solar Program Review Meeting , in Proc., (2003), 1-877
##[4]
R. Birkmire, E. Eser, S. Fields, W. Shafarman, Photovoltaics , Prog., 13 (2005), 1-141
##[5]
Bent, et al, Inorganic Nanocomposite Solar Cells by ALD, GCEP Technical Report , (2006)
##[6]
M. S. Keshner, R. Arya, National Renewable Energy Laboratory, Tech. Rep., http://www.nrel.gov/docs/fy05osti/36846.pdf (2004)
##[7]
Y. J. S. Tyan, E. A. Perez-Albuerne, Efficient thin film CdS/CdTe solar cells, Proceedings of 16th IEEE Photovoltaic Specialists Conference, IEEE Publishing, New York, (1982), 1-794
##[8]
C. Ferekides, J. Britt, Y. Ma, L. Killian, High efficiency CdTe solar cells by close spaced sublimation, Proceedings of Twenty- Third-Photovoltaic-Specialists-Conference IEEE, New York, USA, (1993), 1-389
##[9]
Xuanzhi Wu, High-efficiency polycrystalline CdTe thin-film solar cells, Solar Energy, 77 (2004), 803-814
##[10]
S. Demtsu, J. Sites, Proc of 30th IEEE Photovoltaic Specialist Conference, , (2005), 744-747
##[11]
Nathan S. Lewis, George Crabtree, Basic research needs for solar energy utilization, , (2005), 67-69
##[12]
AMPS-1D (1997), http://www.empl.psu.edu/amps. , , Pennsylvania State University (1997)
##[13]
D. L. Batzner, A. Romeo, H. Zogg, R. Wendt, A. N. Tiwari, Thin Solid Films , 151, 387 (2001)
##[14]
X. Wu, J. C. Keane, R. G. Dhere, C. DeHart, D. S. Albin, A. Duda, T. A. Gessert, S. Asher, D. H. Levi, P. Sheldon, , Proc. of 17th European Photovolt. Sol. Energy Conf., Munich, Germany. (2001)
##[15]
Nowshad Amin, Akira Yamada, Makoto Konagai, , Journal of Applied Physics 41(5A), Part 1, Japanese (2002)
##[16]
M. A. Matin, M. Mannir Aliyu, Abrar H. Quadery, Nowshad Amin, , SOLMAT, 94, 1496 (2010)
##[17]
Nowshad Amin, Kamaruzzaman Sopian, M. Yahya, A. Zaharim, Proceedings of the 8th WSEAS International Conference on POWER SYSTEMS, (PS 2008), Santander, Cantabria, Spain, September 23-25, (2008), 1-299
##[18]
N. Amin, T. Isaka, T. Okamoto, A. Yamada, M. Konagai, , Jpanese Journal of Applied Physics , 38 (1999), 1-4666
##[19]
Xuanzhi Wu, High-efficiency polycrystalline CdTe thin-film solar cells, Solar Energy, 77 (2004), 803-814
##[20]
N. Amin, K. Sopian, M. Konagai , Solar Energy Materials and Solar Cells , , 91 (2007), 1-1202
]
A Fully Fuzzy Approach to Data Envelopment Analysis
A Fully Fuzzy Approach to Data Envelopment Analysis
en
en
Data envelopment analysis (DEA) is a method to evaluate the efficiency of some decision making units which by using one or more inputs will make one or more outputs. In real world, most of the problems don’t have a certain mode. Fuzzy theory is one of the ways of considering uncertainty in the mathematical programming problems. In this study by using this idea, the DEA model on a fully fuzzy mode is proposed. The feature of this proposed model is that it considers 3 situations for problem and solving them simultaneously. The first situation occurs on a desired condition with the highest output and lowest input. The second is made of centric point of inputs and outputs and is analogous with the first condition. The third or undesired situation is when there are upper bound of input and lower bound of output. Results showed that the highest efficiency of some units is 1, so these units are efficient. To collate the efficient units on the proposed method, we can use the obtained centric points for efficiency of units.
238
245
Mostafa
Kazemi
Amir
Alimi
Data envelopment analysis
fully fuzzy model
Decision making unit
Triangular fuzzy number
efficiency.
Article.7.pdf
[
[1]
A. Charnes, W. W. Cooper, E. L. Rhodes, Measuring the efficiency of decision making units, European Journal of Operational Research, 2 (1978), 429-444
##[2]
L. A. Zadeh, Fuzzy Sets, Information and Control, 8 (1965), 338-353
##[3]
A. Azadeh, S. M. Alem, A flexible deterministic, stochastic and fuzzy data envelopment analysis approach for supply chain risk and vendor selection problem: simulation analysis, Expert Systems with Applications, 37 (12) (2010), 7438-7448
##[4]
L. M. ZerafatAngiz, A. Emrouznejad, A. Mustafa, Fuzzy assessment of performance of a decision making units using DEA: a non-radial approach, Expert Systems with Applications, 37 (7) (2010), 5153-5157
##[5]
L. M. ZerafatAngiz, A. Emrouznejad, A. Mustafa, Fuzzy data envelopment analysis: a discrete approach, Expert Systems with Applications, 39 (2012), 2263-2269
##[6]
C. Kao, S. T. Liu, Fuzzy efficiency measures in data envelopment analysis, Fuzzy Sets and Systems, 113 (3) (2000), 427-437
##[7]
C. Kao, S. T. Liu, Data envelopment analysis with missing data: an application to University libraries in Taiwan, Journal of Operational Research Society, 51 (8) (2000), 897-905
##[8]
F. HosseinzadehLotfi, M. AdabitabarFirozja, V. Erfani, Efficiency measures in data envelopment analysis with fuzzy and ordinal data, International Mathematical Forum, 4 (20) (2009), 995-1006
##[9]
G. R. Jahanshahloo, F. HosseinzadehLotfi, R. Shahverdi, M. Adabitabar, M. Rostamy-Malkhalifeh, S. Sohraiee, Ranking DMUs by l1 _ normwith fuzzy data in DEA, Chaos, Solitons and Fractals, 39 (2009), 2294-2302
##[10]
M. Soleimani-damaneh, Establishing the existence of a distance-based upper bound for a fuzzy DEA model using duality, Chaos, Solitons and Fractals, 41 (2009), 485-490
##[11]
Y. K. Juan, A hybrid approach using data envelopment analysis and case-based reasoning for housing refurbishment contractors selection and performance Improvement, Expert Systems with Applications, 36 (3) (2009), 5702-5710
##[12]
S. Lertworasirikul, Fuzzy Data Envelopment Analysis (DEA), Ph.D. Dissertation, Dept. of Industrial Engineering, North Carolina State University (2002)
##[13]
S. Lertworasirikul, S. C. Fang, J. A. Joines, H. L. W. Nuttle, Fuzzy data envelopment analysis (DEA): a possibility approach, Fuzzy Sets and Systems, 139 (2) (2003), 379-394
##[14]
Y. M. Wang, Y. Luo, L. Liang, Fuzzy data envelopment analysis based upon fuzzy arithmetic with an application to performance assessment of manufacturing enterprises, Expert Systems with Applications, 36 (2009), 5205-5211
##[15]
S. Saati, A. Hatami-Marbini, M. Tavana, A data envelopment analysis model with discretionary and non-discretionary factors in fuzzy environments, Int. J. Productivity and Quality Management, 8(1) (2011), 45-63
##[16]
A. Hatami-Marbini, M.Tavana, A. Ebrahimi, A fully fuzzified data envelopment analysis model, International Journal of Information and Decision Sciences, 3(3) (2011), 252-264
##[17]
T. Allahviranloo, F. HosseinzadehLotfi, M. Kh. Kiasary, N. A. Kiani, L. Alizadeh, Solving fully fuzzy linear programming problem by the ranking function, Applied Mathematical Sciences, 2 (2008), 19-32
##[18]
A. Kumar, J. Kaur, P. Singh, Fuzzy optimal solution of fully fuzzy linear programming problems with inequality constraints, International Journal of Mathematical and Computer Sciences, 6 (2010), 37-41
##[19]
M. Dehghan, B. Hashemi, M. Ghatee, Computational methods for solving fully fuzzy linear systems, Applied Mathematics and Computations, 179 (2006), 328-343
##[20]
T. S. Liou, M. J. Wang, Ranking fuzzy numbers with integral value, Fuzzy Sets and Systems, 50 (1992), 247-255
##[21]
V. Kreinovich, A. V. Lakeyev, J. Rohn, P. T. Kahl, Computational Complexity and Feasibility of Data Processing and Interval Computations, Applied Optimization, vol. 10 ( 1998)
##[22]
P. Guo, H. Tanaka, Fuzzy DEA: a perceptual evaluation method, Fuzzy Sets and Systems, 119 (2001), 149-160
##[23]
M. Wen, C. You, R. Kang, A new ranking method to fuzzy data envelopment analysis, Computers and Mathematics with Applications, 59 (2010), 3398-3404
]
Solving Equal-width Wave-burgers Equation by (gg)-expansion Method
Solving Equal-width Wave-burgers Equation by (gg)-expansion Method
en
en
In this paper, we apply the \((\frac{\acute{G}}{G})\)-expansion method to give traveling wave solutions of the third order equal-width wave-Burgers (EW-Burgers) equation. This method is direct, concise and effective and its applications are promising, and it appears to be easier and faster by a symbolic computation system like Maple or Matlab. This work highlights the power of the \((\frac{\acute{G}}{G})\)-expansion method in providing generalized solitary wave solutions of different physical structures.
246
251
Shahnam
Javadi
Eslam
Moradi
Mojtaba
Fardi
Salman
Abbasian
The \((\frac{G'}{G})\)-expansion method
Nonlinear evolution equations
EW-Burgers equation.
Article.8.pdf
[
[1]
J. I. Ramos , Explicit finite difference methods for the EW and RLW equations, Appl. Math. Comput. , 179 (2006), 622-638
##[2]
E. Moradi, H. Varasteh, A. Abdollahzadeh, M. M. Malekshah, The Exp-Function Method for Solving Two Dimensional Sine-Bratu Type Equations, Appl. Math., 5 (2014), 1212-1217
##[3]
A. Bekir, A. Boz, Exact solutions for nonlinear evolution equations using Exp-function method, Phys. Lett. A, 372 (2008), 1619-1625
##[4]
M. Hosseini, H. Abdollahzadeh, M. Abdollahzadeh, Exact Travelling Solutions For The Sixth-Order Boussinesq Equation, The Journal of Mathematics and Computer Science , 2 (2011), 376-387
##[5]
C. T. Yan, A simple transformation for nonlinear waves, Phys. Lett. A , 224 (1996), 77-84
##[6]
E. J. Parkes, Observations on the tanh-coth expansion method for finding solutions to nonlinear evolution equations, Appl. Math. Comput. , 217, 4, 15 (2010), 1749-1754
##[7]
M. L. Wang, Y. B. Zhou, Z. B. Li, Application of a homogeneous balance method to exact solutions of nonlinear equations in mathematical physics, Phys. Lett. A , 216 (1996), 67-75
##[8]
Yu-Xiang Zeng, Yi Zeng, Approximate Solutions of the Q-discrete Burgers Equation, Journal of Mathematics and Computer Science , 7 (2013), 241-248
##[9]
A. Neamaty, B. Agheli, R. Darzi, Solving Fractional Partial Differential Equation by Using Wavelet perational Method, Journal of Mathematics and Computer Science , 7 (2013), 230-240
##[10]
M. L. Wang, X. Z. Li, Extended F-expansion method and periodic wave solutions for the generalized Zakharov equations, Phys. Lett. A, 343 (2005), 48-54
##[11]
M. L. Wang, X. Z. Li, Applications of F-expansion to periodic wave solutions for a new Hamiltonian amplitude equation, Chaos SolitonsFract., 24 (2005), 1257-1268
##[12]
M. Wang, X. Li, J. Zhang, The \((\frac{\acute{G}}{G})\)-expansion method and traveling wave solutions of nonlinear evolution equations in mathematical physics, Phys. Lett. A , 372 (2008), 417-423
##[13]
M. Wang, J. Zhang, X. Li, Application of the \((\frac{\acute{G}}{G})\)-expansion to travelling wave solutions of the Broer-Kaup and the approximate long water wave equations, Appl. Math. Comput., 206 (2008), 321-326
##[14]
I. Aslan, T. Ozis, On the validity and reliability of the \((\frac{\acute{G}}{G})\)-expansion method by using higher-order nonlinear equations, Appl. Math. Comput., 211 (2009), 531-536
##[15]
A. Bekir, Application of the \((\frac{\acute{G}}{G})\)-expansion method for nonlinear evolution equations, Phys. Lett. A , 372 (2008), 3400-3406
]