Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
SsT decomposition method for solving fully fuzzy linear systems
275
280
EN
K.
Jaikumar
Department of Mathematics, Dharmapuram Adhinam
Arts College, Dharmapuram, Mayiladuthurai, Tamilnadu,
India-609001.
kjkdaac@gmail.com
S.
Sunantha
Department of Mathematics, Vivekananda Arts and
Science College for Women, Thenpathi, NSB Nagar,
Sirkali, Tamilnadu, India-609111.
The SST decomposition method for solving system of linear equations make it possible to obtain the values of roots of the system with the specified accuracy as the limit of the sequence of some vectors. In this topic we are going to consider vectors as fuzzy vectors. We have considered a numerical example and tried to find out solution vector x in fuzzified form using method of SST decomposition.
triangular fuzzy numbers,System of linear equations,SST Decomposition Method
http://ijim.srbiau.ac.ir/article_2159.html
http://ijim.srbiau.ac.ir/article_2159_f02828bb562fdd9ffe400b9201b14173.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Numerical solution of fuzzy differential equations under generalized
differentiability by fuzzy neural network
281
297
EN
M.
Mosleh
Department of Mathematics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran.
mosleh@iaufb:ac:ir
In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized characterization Theorem. Then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. Here neural network is considered as a part of large eld called neural computing or soft computing. The model nds the approximated solution of fuzzy differential equation inside of its domain for the close enough neighborhood of the fuzzy initial point. We propose a learning algorithm from the cost function for adjusting of fuzzy weights.
Fuzzy neural networks,Fuzzy dierential equations,Feedforward neural network,Learning
algorithm
http://ijim.srbiau.ac.ir/article_2160.html
http://ijim.srbiau.ac.ir/article_2160_ada214b146352ce06e432998f472270d.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Utilizing a new feed-back fuzzy neural network for solving a system of
fuzzy equations
299
307
EN
A.
Jafarian
Department of Mathematics, Urmia Branch, Islamic
Azad University, Urmia, Iran.
jafarian5594@yahoo.com
S.
Measoomy Nia
Department of Mathematics, Urmia Branch, Islamic
Azad University, Urmia, Iran.
This paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. Our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. This architecture of articial neural networks, can get a real input vector and calculates its corresponding fuzzy output. In order to nd the approximate solution of the fuzzy system that supposedly has a real solution, rst a cost function is dened for the level sets of the fuzzy network and target output. Then a learning algorithm based on the gradient descent method is used to adjust the crisp input signals. The present method is illustrated by several examples with computer simulations.
System of fuzzy equations,Fuzzy feed-back neural network (FFNN),Cost Function,Learning algorithm
http://ijim.srbiau.ac.ir/article_2161.html
http://ijim.srbiau.ac.ir/article_2161_77ac87665945ca1fd46f06217389fa51.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Fully fuzzy linear programming with inequality constraints
309
316
EN
SH.
Nasseri
Department of Mathematics, University of Mazandaran, Babolsar ,Iran.
nasseri@umz.ac.ir
E.
Behmanesh
Department of Mathematics, University of Mazandaran, Babolsar ,Iran.
F.
Taleshian
Department of Mathematics, University of Mazandaran, Babolsar ,Iran.
M.
Abdolalipoor
Department of Mathematics, University of Tabriz,
Tabriz , Iran.
N. A.
TaghiNezhad
Department of Mathematics, University of Mazandaran, Babolsar ,Iran.
Fuzzy linear programming problem occur in many elds such as mathematical modeling, Control theory and Management sciences, etc. In this paper we focus on a kind of Linear Programming with fuzzy numbers and variables namely Fully Fuzzy Linear Programming (FFLP) problem, in which the constraints are in inequality forms. Then a new method is proposed to ne the fuzzy solution for solving (FFLP). Numerical examples are providing to illustrate the method.
Fuzzy numbers,linear programming,Fuzzy linear programming,membership function,Ranking function
http://ijim.srbiau.ac.ir/article_2162.html
http://ijim.srbiau.ac.ir/article_2162_8e908a52ca98e253847ad85ecfc249a5.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Singular constrained linear systems
317
323
EN
M.
Nikuie
Young Researchers and Elite Club, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
nikoie_m@yahoo.com
M. K.
Mirnia
Department of Computer engineering, Tabriz Branch,
Islamic Azad University, Tabriz, Iran.
In the linear system Ax = b the points x are sometimes constrained to lie in a given subspace S of column space of A. Drazin inverse for any singular or nonsingular matrix, exist and is unique. In this paper, the singular consistent or inconsistent constrained linear systems are introduced and the effect of Drazin inverse in solving such systems is investigated. Constrained linear system arise in electrical network theory.
Singular matrix,Drazin inverse,Constrained systems,Bott-Dun inverse
http://ijim.srbiau.ac.ir/article_2163.html
http://ijim.srbiau.ac.ir/article_2163_49d11f17f3e5ef4ceaa52f5c876e1da4.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Some traveling wave solutions of soliton family
325
339
EN
S.
Dhawan
Department Of Mathematics, Dr. B. R. Ambedkar National Institute Of Technology Jalandhar, India.
dhawan311@gmail.com
S.
Kumar
Department Of Mathematics, Dr. B. R. Ambedkar National Institute Of Technology Jalandhar, India.
Solitons are ubiquitous and exist in almost every area from sky to bottom. For solitons to appear, the relevant equation of motion must be nonlinear. In the present study, we deal with the Korteweg-deVries (KdV), Modied Korteweg-de Vries (mKdV) and Regularised LongWave (RLW) equations using Homotopy Perturbation method (HPM). The algorithm makes use of the HPM to determine the initial expansion coecients using the initial value and boundary conditions. The physical structures of the nonlinear dispersive equation have been investigated for different parameters involved. It is shown how the nature of the waves look like in a simple way by considering the value of a certain single combination of constant parameters. The proposed scheme is standard, direct and computerized, which allow us to do complicated and tedious algebraic calculations. The ease of using this method to determine shock or solitary type of solutions, shows its power.
Nonlinear partial differential equations,solitary waves,Homotopy perturbation method (HPM)
http://ijim.srbiau.ac.ir/article_2164.html
http://ijim.srbiau.ac.ir/article_2164_710dad6404c95eb09f5ca85f0a08ee1f.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Strong convergence for variational inequalities and equilibrium
problems and representations
341
354
EN
E.
Soori
Department of Mathematics, University of Isfahan, Isfahan, Iran.
sori.e@lu.ac.ir
We introduce an implicit method for nding a common element of the set of solutions of systems of equilibrium problems and the set of common xed points of a sequence of nonexpansive mappings and a representation of nonexpansive mappings. Then we prove the strong convergence of the proposed implicit schemes to the unique solution of a variational inequality, which is the optimality condition for a minimization problem and is also a common xed point for a sequence of nonexpansive mappings and a representation of nonexpansive mappings.
Representation,Equilibrium problem,fixed point,Nonexpansive mapping,Variational
inequality
http://ijim.srbiau.ac.ir/article_2165.html
http://ijim.srbiau.ac.ir/article_2165_fbdf16b942c288e0fe0aff83616e86d3.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Solving nonlinear Lane-Emden type equations with unsupervised
combined artificial neural networks
355
366
EN
K.
Parand
Department of Computer Sciences, Shahid Beheshti
University, Tehran, Iran.
Z.
Roozbahani
Department of Computer Sciences, Shahid Beheshti
University, Tehran, Iran.
roozbahani2@gmail.com
F.
Bayat Babolghani
Department of Computer Sciences, Shahid Beheshti
University, Tehran, Iran.
In this paper we propose a method for solving some well-known classes of Lane-Emden type equations which are nonlinear ordinary differential equations on the semi-innite domain. The proposed approach is based on an Unsupervised Combined Articial Neural Networks (UCANN) method. Firstly, The trial solutions of the differential equations are written in the form of feed-forward neural networks containing adjustable parameters (the weights and biases); results are then optimized with the combined neural network. The proposed method is tested on series of Lane-Emden differential equations and the results are reported. Afterward, these results are compared with the solution of other methods demonstrating the eciency and applicability of the proposed method.
Lane-Emden type equations,Nonlinear ODE,Semi-infinite domain,Astrophysics,Artificial
neural network,Combined neural network
http://ijim.srbiau.ac.ir/article_2166.html
http://ijim.srbiau.ac.ir/article_2166_354f7534ec6f6f97e1317668d79dc68c.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
On convergence of homotopy analysis method to solve the
Schrodinger equation with a power law nonlinearity
367
374
EN
M. A.
Fariborzi Araghi
Department of Mathematics, Islamic Azad University,
Central Tehran Branch, P. O. Box 13185.768, Tehran,
Iran.
m_fariborzi@iauctb.ac.ir
S.
Naghshband
Department of Mathematics, Islamic Azad University,
Central Tehran Branch, P. O. Box 13185.768, Tehran,
Iran.
In this paper, the homotopy analysis method (HAM) is considered to obtain the solution of the Schrodinger equation with a power law nonlinearity. For this purpose, a theorem is proved to show the convergence of the series solution obtained from the proposed method. Also, an example is solved to illustrate the eciency of the mentioned algorithm and the h-curve is plotted to determine the region of convergence.
Schrodinger equation,Power law nonlinearity,Homotopy analysis method (HAM),Convergence
http://ijim.srbiau.ac.ir/article_2167.html
http://ijim.srbiau.ac.ir/article_2167_886df42458e71c96bf5b5a340137d655.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
The effects of outside board on firm value in Tehran Stock Exchange
from the perspective of information transaction costs
375
386
EN
S.
Jabbarzadeh Kangarlouei
Department of Accounting, Science and Research
Branch, Islamic Azad University, West Azarbyjan, Iran.
jabbarzadeh.s@gmail.com
B.
Kavasi
Department of Accounting, Science and Research
Branch, Islamic Azad University, West Azarbyjan, Iran.
M.
Motavassel
Department of Accounting, Science and Research
Branch, Islamic Azad University, West Azarbyjan, Iran.
The aim of this study is to investigate the effects of outside board on rm value in Tehran Stock Exchange (TSE) from the perspective of information transaction costs. To do so, a sample of 96 firms listed in TSE is selected to be studied during the period of 2003-2012. Tobin q ratio is used to measure rm's value and bid-ask spread for information transaction costs. In addition to these variables, four control variables are adapted namely rm's characteristic, age, size and duality. The results of the study show that there is not a signicant relationship between outside board and firm's value. Investigating the relationship between outside board and rm's value, the results indicate that only in food and non-metal industries, there is a negative relationship between outside board and firm's performance. Therefore, it can be concluded that not in all of industries outside board affects rm's value. Further, results do not prove the effects of outside board on information transaction cost. In addition, the results do not support that information transaction cost aect rm's value. Finally, the results also suggest that independence and presence of outside board of director member does not a effect firm's value in rms with lower information transaction cost.
Outside Board,Firm Value,Information Transaction Costs and Tehran Stock Exchange
http://ijim.srbiau.ac.ir/article_2168.html
http://ijim.srbiau.ac.ir/article_2168_a6fb1a37cb15562c84d0e23ae0ae7277.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Groups performance ranking based on inefficiency sharing
387
395
EN
M.
Momeni
Department of Industrial Management, University of
Tehran, Iran.
G. R.
Jahanshahloo
Faculty of Mathematical Science and Computer Engineering, University for Teacher Education, Iran.
M.
Rostamy Malkhalifeh
Department of Mathematics, Science and Research
Branch, Islamic Azad University ,Iran.
S.
Razavi
Department of Industrial Management, University of
Tehran, Iran.
K.
Yakideh
Department of Industrial Management, University of
Tehran, Iran.
yakideh@ymail.com
In the real world there are groups which composed of independent units. The conventional data envelopment analysis(DEA) model treats groups as units, ignoring the operation of individual units within each group.The current paper, investigates parallel system network approach proposed by Kao and modifies it. As modied Kao' model is more eligible to recognize ecient groups, a new ranking method is proposed based on a model which calculates eciencies with additional constraint that made model share constant ineciency among groups.To show advantages, modies model is applied to eciency calculation of both articial and real groups and results is compared with conventional DEA model and parallel system network model as well.Finally it is shown by tow numerical and empirical examples that ecient groups recognized by modied model how can be ranked according to proposed ranking model.
Data envelopment analysis,Group Ranking,Network DEA,Parallel Systems Efficiency,Efficient Groups
http://ijim.srbiau.ac.ir/article_2169.html
http://ijim.srbiau.ac.ir/article_2169_89ad590a5332caa8d31bcf740e9f38fe.pdf
Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Industrial Mathematics
2008-5621
2008-563X
5
4
2013
12
01
Ranking Network-Structured Decision-Making Units and Its Application in Bank Branches
397
402
EN
M.
Shahriari
Faculty of Management, UAE branch, Islamic Azad University, Dubai, UAE.
shahriari@iau.ae
Data envelopment analysis (DEA) is a method used for measuring the efficiency of decision-making units. Unlike the standard models, which assume decision-making units to be a black box, network data envelopment analysis focuses on the internal structure of these units. Some researchers have developed a two-stage method where all the inputs are entirely used in the first stage, producing outputs which are subsequently fed as inputs to the second stage. These indices are introduced as intermediate indices. Here, it is assumed that congruent decision-making units have a two-stage serial structure. In this structure, the first stage and second stages act as the supplier and the consumer of resources respectively. Two ranking models based on the efficiency cloud and the common set of weights concepts were developed for ranking network-structured decision-making units. In the practical example presented in this study, 25 bank branches were ranked using the two-stage method.
Data envelopment analysis (DEA),Two-stage,Ranking
http://ijim.srbiau.ac.ir/article_8806.html
http://ijim.srbiau.ac.ir/article_8806_4d2fab8530e70ea63f1eaa430f273767.pdf