eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-29
2
2
0
10.22111/ijfs.2005.3123
3123
Cover vol.2, no.2 October 2005
http://ijfs.usb.ac.ir/article_3123_22bd51a9452559d8810ff5b8a8a8c882.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
1
13
10.22111/ijfs.2005.477
477
مقاله پژوهشی
INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES
YONG SOO KIM
kystj@dju.ac.kr
1
Z. ZENN BIEN
zbien@ee.kaist.ac.kr
2
DIVISION OF COMPUTER ENGINEERING, DAEJEON UNIVERSITY, DAEJEON, 300-716, KOREA
DEPARTMENT OF ELECRICAL ENGINEERING AND COMPUTER SCIENCE, KAIST, DAEJEON, 305-701, KOREA
The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC neural networks are the supervised neural networkswhich use the fuzzified versions of Learning Vector Quantization (LVQ). In this paper,several important adaptive learning algorithms are compared from the viewpoint of structure andlearning rule. The performances of several adaptive learning algorithms are compared usingIris data set.
http://ijfs.usb.ac.ir/article_477_b026c6b686fee4da511735fefc3be005.pdf
Neural Networks
Fuzzy Logic
Fuzzy neural networks
Learning rule
Fuzzification
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
15
20
10.22111/ijfs.2005.478
478
مقاله پژوهشی
POINTWISE PSEUDO-METRIC ON THE L-REAL LINE
Fu-Gui Shi
fuguishi@bit.edu.cn or f.g.shi@263.net
1
Department of Mathematics, Beijing Institute of Technology, Beijing, 100081, P.R. China
In this paper, a pointwise pseudo-metric function on the L-realline is constructed. It is proved that the topology induced by this pointwisepseudo-metric is the usual topology.
http://ijfs.usb.ac.ir/article_478_5d05c3a1bafafbe167cbaf76af5b1eec.pdf
L-topology
Pointwise pseudo-metric
The L-real line
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
21
29
10.22111/ijfs.2005.479
479
مقاله پژوهشی
DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED
PROGRAMMING APPROACH
SAEED RAMEZANZADEH
ramezanzadeh_s@yahoo.com
1
AZIZOLLAH MEMARIANI
a_memariani@yahoo.com
2
SABER SAATI
ssaatim@yahoo.com
3
DEPARTMENT OF MATHEMATICS, POLICE UNIVERSITY, TEHRAN, IRAN
DEPARTMENT OF INDUSTRIAL ENGINEERING, BU-ALI SINA UNIVERSITY, HAMEDAN, IRAN
DEPARTMENT OF MATHEMATICS, TEHRAN NORTH BRANCH, ISLAMIC AZAD UNIVERSITY, TEHRAN, IRAN
In this paper, we deal with fuzzy random variables for inputs andoutputs in Data Envelopment Analysis (DEA). These variables are considered as fuzzyrandom flat LR numbers with known distribution. The problem is to find a method forconverting the imprecise chance-constrained DEA model into a crisp one. This can bedone by first, defuzzification of imprecise probability by constructing a suitablemembership function, second, defuzzification of the parameters using an α-cut andfinally, converting the chance-constrained DEA into a crisp model using the methodof Cooper [4].
http://ijfs.usb.ac.ir/article_479_1ced6022a8946914d082e27726e96216.pdf
Data Envelopment Analysis
Chance-constrained DEA
Fuzzy random
variable
Triangular fuzzy number
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
31
36
10.22111/ijfs.2005.480
480
مقاله پژوهشی
A SHORT NOTE ON THE RELATIONSHIP BETWEEN GOAL PROGRAMMING AND FUZZY PROGRAMMING FOR
VECTORMAXIMUM PROBLEMS
M. A. Yaghoobi
yaghoobi@mail.uk.ac.ir
1
M. Tamiz
mehrdad.tamiz@port.ac.uk
2
Faculty of Mathematics and Computer Sciences, University of Kerman, Kerman, Iran
Department of Mathematics, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE, UK
A theorem was recently introduced to establish a relationship betweengoal programming and fuzzy programming for vectormaximum problems.In this short note it is shown that the relationship does not exist underall circumstances. The necessary correction is proposed.
http://ijfs.usb.ac.ir/article_480_7b6cf03b7e38d16e82e65f5ff0221149.pdf
Fuzzy programming
Goal programming
Fuzzy multi-objective programming
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
37
43
10.22111/ijfs.2005.481
481
مقاله پژوهشی
A METHOD FOR SOLVING FUZZY LINEAR SYSTEMS
Saeid Abbasbandy
saeid@abbasbandy.com
1
Magid Alavi
alavi_ma2004@yahoo.com
2
Department of Mathematics, Imam Khomeini International University, Ghazvin, 34194, Iran
Department Of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, 14778, Iran
In this paper we present a method for solving fuzzy linear systemsby two crisp linear systems. Also necessary and sufficient conditions for existenceof solution are given. Some numerical examples illustrate the efficiencyof the method.
http://ijfs.usb.ac.ir/article_481_7287fa5649070a2665e500ffa0d779f1.pdf
Symmetric fuzzy linear system
Fuzzy linear system
Nonnegative
matrix
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
45
57
10.22111/ijfs.2005.482
482
مقاله پژوهشی
A NEURO-FUZZY TECHNIQUE FOR DISCRIMINATION BETWEEN INTERNAL FAULTS AND MAGNETIZING INRUSH CURRENTS IN TRANSFORMERS
HASSAN KHORASHADI-ZADEH
hkhorashadi@birjand.ac.ir
1
MOHAMMAD REZA AGHAEBRAHIMI
aghaebrahimi@birjand.ac.ir
2
DEPARTMENT OF POWER ENGINEERING, UNIVERSITY OF BIRJAND, IRAN
DEPARTMENT OF POWER ENGINEERING, UNIVERSITY OF BIRJAND, IRAN
This paper presents the application of the fuzzy-neuro method toinvestigate transformer inrush current. Recently, the frequency environment ofpower systems has been made more complicated and the magnitude of the secondharmonic in inrush current has been decreased because of the improvement of caststeel. Therefore, traditional approaches will likely mal-operate in the case ofmagnetizing inrush with low second component and internal faults with highsecond harmonic. The proposed scheme enhances the inrush detection sensitivity ofconventional techniques by using a fuzzy-neuro approach. Details of the designprocedure and the results of performance studies with the proposed detector aregiven in the paper. The results of performance studies show that the proposedalgorithm is fast and accurate.
http://ijfs.usb.ac.ir/article_482_1e80e370d9421c96322a24101a56e88e.pdf
This paper presents the application of the fuzzy-neuro method to
investigate transformer inrush current. Recently
the frequency environment of
power systems has been made more complicated and the magnitude of the second
harmonic in inrush current has been decreased because of the improvement of cast
steel. Therefore
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
59
70
10.22111/ijfs.2005.483
483
مقاله پژوهشی
MEASURING SOFTWARE PROCESSES PERFORMANCE BASED ON FUZZY MULTI AGENT MEASUREMENTS
MIR ALI SEYYEDI
seyyedi@behpardaz.net
1
MOHAMMA TESHNEHLAB
teshnehlab@eet.kntu.ac.ir
2
FEREIDOON SHAMS
f.shams@agri-jahad.org
3
COMPUTER - SOFTWARE DEPARTMENT OF SCIENCES & RESEARCH, TEHRAN, IRAN
DEPARTMENT OF CONTROL, KHAJEH NASIR TECHNICAL UNIVERSITY, TEHRAN, IRAN
COMPUTER - SOFTWARE DEPARTMENT OF SCIENCES & RESEARCH, TEHRAN, IRAN
The present article discusses and presents a new and comprehensive approachaimed at measuring the maturity and quality of software processes. This method has beendesigned on the basis of the Software Capability Maturity Model (SW-CMM) and theMulti-level Fuzzy Inference Model and is used as a measurement and analysis tool. Among themost important characteristics of this method one can mention simple usage, accuracy,quantitative measures and comparability. Fuzzy logic-based tools are designed to providesuch functions.
http://ijfs.usb.ac.ir/article_483_1a16c25bab856f9572c194173aa0d2ad.pdf
Software capability maturity model
Goal/ Question / Metric method
Key
process areas
Fuzzy System
Multi level fuzzy inference model
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-21
2
2
71
80
10.22111/ijfs.2005.484
484
مقاله پژوهشی
ON ANTI FUZZY IDEALS IN NEAR-RINGS
Kyung Ho Kim
ghkim@chungju.ac.kr
1
Young Bae Jun
ybjun@nongae.gsnu.ac.kr
2
Yong Ho Yon
yhyonkr@hanmail.net
3
Department of Mathematics, Chungju National University, Chungju 380-702, Korea
Department of Mathematics Education, Gyeongsang National University, Chinju 660-701, Korea
Department of Mathematics, Chungbuk National University, Cheongju 361-763, Korea
In this paper, we apply the Biswas’ idea of anti fuzzy subgroups toideals of near-rings. We introduce the notion of anti fuzzy ideals of near-rings,and investigate some related properties.
http://ijfs.usb.ac.ir/article_484_4fb52b20fde87511ab0820dd4e44ad02.pdf
near-ring
anti fuzzy subnear-ring
anti (fuzzy) right (resp. left) ideals
anti level right (resp. left) ideals
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2005-10-29
2
2
83
90
10.22111/ijfs.2005.3124
3124
Persian-translation vol.2, no.2 October 2005
http://ijfs.usb.ac.ir/article_3124_0cb94c10119b1b62f819725b5ccefa3b.pdf