University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
29
Cover vol.2, no.2 October 2005
0
EN
10.22111/ijfs.2005.3123
http://ijfs.usb.ac.ir/article_3123.html
http://ijfs.usb.ac.ir/article_3123_22bd51a9452559d8810ff5b8a8a8c882.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES
1
13
EN
YONG SOO
KIM
DIVISION OF COMPUTER ENGINEERING, DAEJEON UNIVERSITY, DAEJEON, 300-716,
KOREA
kystj@dju.ac.kr
Z.
ZENN BIEN
DEPARTMENT OF ELECRICAL ENGINEERING AND COMPUTER SCIENCE, KAIST,
DAEJEON, 305-701, KOREA
zbien@ee.kaist.ac.kr
10.22111/ijfs.2005.477
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.
Neural Networks,Fuzzy Logic,Fuzzy neural networks,Learning rule,Fuzzification
http://ijfs.usb.ac.ir/article_477.html
http://ijfs.usb.ac.ir/article_477_b026c6b686fee4da511735fefc3be005.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
POINTWISE PSEUDO-METRIC ON THE L-REAL LINE
15
20
EN
Fu-Gui
Shi
Department of Mathematics, Beijing Institute of Technology, Beijing,
100081, P.R. China
fuguishi@bit.edu.cn or f.g.shi@263.net
10.22111/ijfs.2005.478
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.
L-topology,Pointwise pseudo-metric,The L-real line
http://ijfs.usb.ac.ir/article_478.html
http://ijfs.usb.ac.ir/article_478_5d05c3a1bafafbe167cbaf76af5b1eec.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED
PROGRAMMING APPROACH
21
29
EN
SAEED
RAMEZANZADEH
DEPARTMENT OF MATHEMATICS, POLICE UNIVERSITY, TEHRAN, IRAN
ramezanzadeh_s@yahoo.com
AZIZOLLAH
MEMARIANI
DEPARTMENT OF INDUSTRIAL ENGINEERING, BU-ALI SINA UNIVERSITY,
HAMEDAN, IRAN
a_memariani@yahoo.com
SABER
SAATI
DEPARTMENT OF MATHEMATICS, TEHRAN NORTH BRANCH, ISLAMIC AZAD
UNIVERSITY, TEHRAN, IRAN
ssaatim@yahoo.com
10.22111/ijfs.2005.479
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].
Data Envelopment Analysis,Chance-constrained DEA,Fuzzy random
variable,Triangular fuzzy number
http://ijfs.usb.ac.ir/article_479.html
http://ijfs.usb.ac.ir/article_479_1ced6022a8946914d082e27726e96216.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
A SHORT NOTE ON THE RELATIONSHIP BETWEEN GOAL PROGRAMMING AND FUZZY PROGRAMMING FOR
VECTORMAXIMUM PROBLEMS
31
36
EN
M. A.
Yaghoobi
Faculty of Mathematics and Computer Sciences, University of
Kerman, Kerman, Iran
yaghoobi@mail.uk.ac.ir
M.
Tamiz
Department of Mathematics, University of Portsmouth, Buckingham Building,
Lion Terrace, Portsmouth, PO1 3HE, UK
mehrdad.tamiz@port.ac.uk
10.22111/ijfs.2005.480
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.
Fuzzy programming,Goal programming,Fuzzy multi-objective programming
http://ijfs.usb.ac.ir/article_480.html
http://ijfs.usb.ac.ir/article_480_7b6cf03b7e38d16e82e65f5ff0221149.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
A METHOD FOR SOLVING FUZZY LINEAR SYSTEMS
37
43
EN
Saeid
Abbasbandy
Department of Mathematics, Imam Khomeini International University,
Ghazvin, 34194, Iran
saeid@abbasbandy.com
Magid
Alavi
Department Of Mathematics, Science and Research Branch, Islamic
Azad University, Tehran, 14778, Iran
alavi_ma2004@yahoo.com
10.22111/ijfs.2005.481
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.
Symmetric fuzzy linear system,Fuzzy linear system,Nonnegative
matrix
http://ijfs.usb.ac.ir/article_481.html
http://ijfs.usb.ac.ir/article_481_7287fa5649070a2665e500ffa0d779f1.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
A NEURO-FUZZY TECHNIQUE FOR DISCRIMINATION BETWEEN INTERNAL FAULTS AND MAGNETIZING INRUSH CURRENTS IN TRANSFORMERS
45
57
EN
HASSAN
KHORASHADI-ZADEH
DEPARTMENT OF POWER ENGINEERING, UNIVERSITY OF BIRJAND,
IRAN
hkhorashadi@birjand.ac.ir
MOHAMMAD REZA
AGHAEBRAHIMI
DEPARTMENT OF POWER ENGINEERING, UNIVERSITY OF
BIRJAND, IRAN
aghaebrahimi@birjand.ac.ir
10.22111/ijfs.2005.482
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.
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
http://ijfs.usb.ac.ir/article_482.html
http://ijfs.usb.ac.ir/article_482_1e80e370d9421c96322a24101a56e88e.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
MEASURING SOFTWARE PROCESSES PERFORMANCE BASED ON FUZZY MULTI AGENT MEASUREMENTS
59
70
EN
MIR ALI
SEYYEDI
COMPUTER - SOFTWARE DEPARTMENT OF SCIENCES & RESEARCH, TEHRAN,
IRAN
seyyedi@behpardaz.net
MOHAMMA
TESHNEHLAB
DEPARTMENT OF CONTROL, KHAJEH NASIR TECHNICAL UNIVERSITY,
TEHRAN, IRAN
teshnehlab@eet.kntu.ac.ir
FEREIDOON
SHAMS
COMPUTER - SOFTWARE DEPARTMENT OF SCIENCES & RESEARCH, TEHRAN,
IRAN
f.shams@agri-jahad.org
10.22111/ijfs.2005.483
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.
Software capability maturity model,Goal/ Question / Metric method,Key
process areas,Fuzzy System,Multi level fuzzy inference model
http://ijfs.usb.ac.ir/article_483.html
http://ijfs.usb.ac.ir/article_483_1a16c25bab856f9572c194173aa0d2ad.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
21
ON ANTI FUZZY IDEALS IN NEAR-RINGS
71
80
EN
Kyung Ho
Kim
Department of Mathematics, Chungju National University, Chungju
380-702, Korea
ghkim@chungju.ac.kr
Young Bae
Jun
Department of Mathematics Education, Gyeongsang National University,
Chinju 660-701, Korea
ybjun@nongae.gsnu.ac.kr
Yong Ho
Yon
Department of Mathematics, Chungbuk National University, Cheongju
361-763, Korea
yhyonkr@hanmail.net
10.22111/ijfs.2005.484
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.
near-ring,anti fuzzy subnear-ring,anti (fuzzy) right (resp. left) ideals,anti level right (resp. left) ideals
http://ijfs.usb.ac.ir/article_484.html
http://ijfs.usb.ac.ir/article_484_4fb52b20fde87511ab0820dd4e44ad02.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
2
2
2005
10
29
Persian-translation vol.2, no.2 October 2005
83
90
EN
10.22111/ijfs.2005.3124
http://ijfs.usb.ac.ir/article_3124.html
http://ijfs.usb.ac.ir/article_3124_0cb94c10119b1b62f819725b5ccefa3b.pdf