eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-01
9
1
0
10.22111/ijfs.2012.2816
2816
Cover vol. 9, no.1, February 2012
http://ijfs.usb.ac.ir/article_2816_9276302627a083223f091bfc721de91a.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-10
9
1
1
19
10.22111/ijfs.2012.221
221
مقاله پژوهشی
APPLICATION OF TABU SEARCH FOR SOLVING THE
BI-OBJECTIVE WAREHOUSE PROBLEM IN
A FUZZY ENVIRONMENT
Anila Gupta
anilasingal@gmail.com
1
Amit Kumar
amit rs iitr@yahoo.com
2
Mahesh Kumar Sharma
mksharma@thapar.edu
3
School of Mathematics and Computer Applications, Thapar Univer-
sity, Patiala-147004, India
School of Mathematics and Computer Applications, Thapar University,
Patiala-147004, India
School of Mathematics and Computer Applications, Thapar
University, Patiala-147004, India
The bi-objective warehouse problem in a crisp environment is often not eective in dealing with the imprecision or vagueness in the values of the problem parameters. To deal with such situations, several researchers have proposed that the parameters be represented as fuzzy numbers. We describe a new algorithm for fuzzy bi-objective warehouse problem using a ranking function followed by an application of tabu search. The method is illustrated on a numerical example, demonstrating the eectiveness of the tabu search method. Numerical results are compared for both fuzzy and crisp versions of the problem.
http://ijfs.usb.ac.ir/article_221_2400536ae1bcebd857003631acf8ca86.pdf
Trapezoidal fuzzy numbers
Bi-objective warehouse problem
Ecient
solution
Tabu search
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-10
9
1
21
37
10.22111/ijfs.2012.223
223
مقاله پژوهشی
FUZZY GRAVITATIONAL SEARCH ALGORITHM AN
APPROACH FOR DATA MINING
Seyed Hamid Zahiri
hzahiri@@birjand.ac.ir
1
Department of Electrical Engineering, Faculty of Engineering,
Birjand University, Birjand, Iran
The concept of intelligently controlling the search process of gravitational search algorithm (GSA) is introduced to develop a novel data mining technique. The proposed method is called fuzzy GSA miner (FGSA-miner). At first a fuzzy controller is designed for adaptively controlling the gravitational coefficient and the number of effective objects, as two important parameters which play major roles on search process of GSA. Then the improved GSA (namely Fuzzy-GSA) is employed to construct a novel data mining algorithm for classification rule discovery from reference data sets. Extensive experimental results on different benchmarks and a practical pattern recognition problem with nonlinear, overlapping class boundaries and different feature space dimensions are provided to show the powerfulness of the proposed method. The comparative results illustrate that performance of the proposed FGSA-miner considerably outperforms the standard GSA. Also it is shown that the performance of the FGSA-miner is comparable to, sometimes better than those of the CN2 (a traditional data mining method) and similar approach which have been designed based on other swarm intelligence algorithms (ant colony optimization and particle swarm optimization) and evolutionary algorithm (genetic algorithm).
http://ijfs.usb.ac.ir/article_223_8aafe00e6254010a39a49144e87459eb.pdf
Gravitational search algorithm
Fuzzy controller
Data mining
Rule
based classifier
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-10
9
1
39
48
10.22111/ijfs.2012.224
224
مقاله پژوهشی
A NEW APPROACH TO STABILITY ANALYSIS OF FUZZY
RELATIONAL MODEL OF DYNAMIC SYSTEMS
Arya Aghili Ashtiani
arya.aghili@aut.ac.ir
1
Sayyed Kamaloddin Yadavar Nikravesh
nikravsh@aut.ac.ir
2
Department of Electrical Engineering, Amirkabir University
of Technology (AUT), P. O. Box 15914, Tehran, Iran
Department of Electrical Engineering, Amirk-
abir University of Technology (AUT), P. O. Box 15914, Tehran, Iran
This paper investigates the stability analysis of fuzzy relational dynamic systems. A new approach is introduced and a set of sufficient conditions is derived which sustains the unique globally asymptotically stable equilibrium point in a first-order fuzzy relational dynamic system with sumproduct fuzzy composition. This approach is also investigated for other types of fuzzy relational composition.
http://ijfs.usb.ac.ir/article_224_c42486dad4820bcdd105fb3f70d965ff.pdf
Fuzzy relational dynamic system (FRDS)
Fuzzy relational model
(FRM)
Linguistic stability analysis
Fuzzy relational stability
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-10
9
1
49
60
10.22111/ijfs.2012.225
225
مقاله پژوهشی
ON SOLUTION OF A CLASS OF FUZZY BVPs
Omid Solaymani Fard
osfard@du.ac.ir, omidsfard@gmail.com
1
Amin Esfahani
amin@impa.br, esfahani@du.ac.ir
2
Ali Vahidian Kamyad
avkamyad@math.um.ac.ir
3
School of Mathematics and Computer Science, Damghan Uni-
versity, Damghan, Iran
School of Mathematics and Computer Science, Damghan University,
Damghan, Iran
Department of Mathematics, Ferdowsi University of Mashhad,
Mashhad, Iran
This paper investigates the existence and uniqueness of solutions to rst-order nonlinear boundary value problems (BVPs) involving fuzzy dif- ferential equations and two-point boundary conditions. Some sucient condi- tions are presented that guarantee the existence and uniqueness of solutions under the approach of Hukuhara dierentiability.
http://ijfs.usb.ac.ir/article_225_64b3d7d1d93425ef5d2a6e2adb0af34c.pdf
Fuzzy numbers
Fuzzy dierential equations
Boundary value
problems
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-10
9
1
61
77
10.22111/ijfs.2012.226
226
مقاله پژوهشی
SECURING INTERPRETABILITY OF FUZZY MODELS FOR
MODELING NONLINEAR MIMO SYSTEMS USING
A HYBRID OF EVOLUTIONARY ALGORITHMS
Mojtaba Eftekhari
m.eftekhari59@gmail.com
1
Mahdi Eftekhari
m.eftekhari@uk.ac.ir
2
Maryam Majidi
majena67@yahoo.com
3
Hossein Nezamabadi pour
nezam h@yahoo.com
4
Faculty of Islamic Azad University, Sirjan branch, ,Sirjan, Ker-
man, Iran
Department of Computer Engineering, School of Engineering,
Shahid Bahonar University of Kerman, Kerman, Iran
Department of Computer Engineering, School of Engineering, Shahid
Bahonar University of Kerman, Kerman, Iran
Department of Electrical Engineering, School of Engi-
neering, Shahid Bahonar University of Kerman, Kerman, Iran
In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level interpretability requirements of fuzzy models is especially a complicated task in case of modeling nonlinear MIMO systems. Due to these multiple and conicting objectives, MOGA is applied to yield a set of candidates as compact, transparent and valid fuzzy models. Also, MOGA is combined with a powerful search algorithm namely Dierential Evolution (DE). In the proposed algorithm, MOGA performs the task of membership function tuning as well as rule base identi cation simultaneously while DE is utilized only for linear parameter identi cation. Practical applicability of the proposed algorithm is examined by two nonlinear system modeling prob- lems used in the literature. The results obtained show the eectiveness of the proposed method.
http://ijfs.usb.ac.ir/article_226_cc28b7c778fbedd749288307752c17c8.pdf
Multi-objective
Evolutionary
Fuzzy identication
Compact
Inter-
pretability
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-11
9
1
79
95
10.22111/ijfs.2012.227
227
مقاله پژوهشی
ESTIMATORS BASED ON FUZZY RANDOM VARIABLES AND
THEIR MATHEMATICAL PROPERTIES
M. G. Akbari
mga13512@yahoo.com
1
M. Khanjari Sadegh
g_z_akbari@yahoo.com
2
Department of Statistics, Faculty of Sciences, University of Birjand,
Southern Khorasan, Birjand
Department of Statistics, Faculty of Sciences, University of
Birjand, Southern Khorasan, Birjand
In statistical inference, the point estimation problem is very crucial and has a wide range of applications. When, we deal with some concepts such as random variables, the parameters of interest and estimates may be reported/observed as imprecise. Therefore, the theory of fuzzy sets plays an important role in formulating such situations. In this paper, we rst recall the crisp uniformly minimum variance unbiased (UMVU) and Bayesian estimators and then develop the concept of fuzzy estimators for fuzzy parameters based on fuzzy random variables.
http://ijfs.usb.ac.ir/article_227_b17c576a5e5de627e505d9f09b0d933c.pdf
Fuzzy random variable
Fuzzy parameter
Signed distance
L2- metric
Fuzzy estimator
Fuzzy unbiased estimator
Fuzzy sufficient estimator
Fuzzy risk function
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-11
9
1
97
108
10.22111/ijfs.2012.228
228
مقاله پژوهشی
A NEW METHOD TO REDUCE TORQUE RIPPLE IN
SWITCHED RELUCTANCE MOTOR USING
FUZZY SLIDING MODE
S. R. Mousavi-Aghdam
rmousavi@tabrizu.ac.ir
1
M. B. B. Sharifian
sharifian@tabrizu.ac.ir
2
M. R. Banaei
m.banaei@azaruniv.edu
3
Faculty of electrical and computer engineering, University
of Tabriz, Tabriz, Iran
Faculty of electrical and computer engineering, University of
Tabriz, Tabriz, Iran
Department of electrical engineering, Faculty of engineering, azarbai-
jan, University of tarbiat moallem, Tabriz, Iran
This paper presents a new control structure to reduce torque ripple in switched reluctance motor. Although SRM possesses many advantages in motor structure, it suers from large torque ripple that causes some problems such as vibration and acoustic noise. In this paper another control loop is added and torque ripple is de ned as an objective function. By using fuzzy sliding mode strategy, the DC link voltage is adjusted to optimize the objective function. Simulation results have demonstrated the proposed control method.
http://ijfs.usb.ac.ir/article_228_eda29a4d8485fce43ad3b0b5e35789ed.pdf
Fuzzy sliding control
Switched Reluctance Motor
Torque ripple re-
duction
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-11
9
1
109
119
10.22111/ijfs.2012.229
229
مقاله پژوهشی
FUZZY SOFT MATRIX THEORY AND ITS APPLICATION IN
DECISION MAKING
Naim Cagman
ncagman@gop.edu.tr
1
Serdar Enginoglu
serdarenginoglu@gop.edu.tr
2
Department of Mathematics, Faculty of Arts and Sciences, Gazios-
manpasa University, 60250 Tokat, Turkey
Department of Mathematics, Faculty of Arts and Sciences, Gazios-
manpasa University, 60250 Tokat, Turkey
In this work, we define fuzzy soft ($fs$) matrices and theiroperations which are more functional to make theoretical studies inthe $fs$-set theory. We then define products of $fs$-matrices andstudy their properties. We finally construct a $fs$-$max$-$min$decision making method which can be successfully applied to theproblems that contain uncertainties.
http://ijfs.usb.ac.ir/article_229_b6d292816ccde2e91d91920714cb6245.pdf
Fuzzy soft sets
Fuzzy soft matrix
Products of fuzzy soft matrices
Fuzzy soft max-min decision making
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-11
9
1
121
140
10.22111/ijfs.2012.230
230
مقاله پژوهشی
FUZZY LINEAR REGRESSION BASED ON
LEAST ABSOLUTES DEVIATIONS
S. M. Taheri
sm_taheri@yahoo.com
1
M. Kelkinnama
m_ kelkinnama@yahoo.com
2
Department of Mathematical Sciences, Isfahan University of Technology, Isfahan 84156-83111, Iran and Department of Statistics, School of Mathematical
Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
Department of Mathematical Sciences, Isfahan University of Technology, Isfahan 84156-83111, Iran
This study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. A least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. The proposed approach, which can deal with both symmetric and non-symmetric fuzzy observations, is compared with several existing models by three goodness of t criteria. Three well-known data sets including two small data sets as well as a large data set are employed for such comparisons.
http://ijfs.usb.ac.ir/article_230_d59e96e289e06159aecc01cdcd61a9dd.pdf
Fuzzy regression
Least absolutes deviations
Metric on fuzzy numbers
Similarity measure
Goodness of fit
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-11
9
1
141
158
10.22111/ijfs.2012.231
231
مقاله پژوهشی
TRANSPORT ROUTE PLANNING MODELS BASED
ON FUZZY APPROACH
Julio Brito
jbrito@ull.es
1
Jose A. Moreno
jamoreno@ull.es
2
Jose L. Verdegay
verdegay@decsai.ugr.es
3
I. U. D. R., University of La Laguna, E-38271 Tenerife, Spain
I. U. D. R., University of La Laguna, E-38271 Tenerife, Spain
Department C. C. I. A., University of Granada, E-18071 Granada,
Spain
Transport route planning is one of the most important and frequent activities in supply chain management. The design of information systems for route planning in real contexts faces two relevant challenges: the complexity of the planning and the lack of complete and precise information. The purpose of this paper is to nd methods for the development of transport route planning in uncertainty decision making contexts. The paper uses an approximation that integrates a speci c fuzzy-based methodology from Soft Computing. We present several fuzzy optimization models that address the imprecision and/or exibility of some of its components. These models allow transport route planning problems to be solve with the help of metaheuristics in a concise way. A simple numerical example is shown to illustrate this approach.
http://ijfs.usb.ac.ir/article_231_7ebf6519fbcb9484fdaa9a6e8d293100.pdf
Fuzzy optimization
Route planning
Soft computing
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2012-02-01
9
1
161
170
10.22111/ijfs.2012.2817
2817
Persian-translation vol. 9, no.1, February 2012
http://ijfs.usb.ac.ir/article_2817_2daa4ebcebc8bddd67ee46bf11e33390.pdf