2018-02-25T01:08:41Z
http://ijfs.usb.ac.ir/?_action=export&rf=summon&issue=95
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
Cover vol.2, no.2 October 2005
2005
10
29
0
http://ijfs.usb.ac.ir/article_3123_22bd51a9452559d8810ff5b8a8a8c882.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES
YONG SOO
KIM
Z.
ZENN BIEN
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
2005
10
21
1
13
http://ijfs.usb.ac.ir/article_477_b026c6b686fee4da511735fefc3be005.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
POINTWISE PSEUDO-METRIC ON THE L-REAL LINE
Fu-Gui
Shi
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
2005
10
21
15
20
http://ijfs.usb.ac.ir/article_478_5d05c3a1bafafbe167cbaf76af5b1eec.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
DATA ENVELOPMENT ANALYSIS WITH FUZZY RANDOM INPUTS AND OUTPUTS: A CHANCE-CONSTRAINED
PROGRAMMING APPROACH
SAEED
RAMEZANZADEH
AZIZOLLAH
MEMARIANI
SABER
SAATI
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
2005
10
21
21
29
http://ijfs.usb.ac.ir/article_479_1ced6022a8946914d082e27726e96216.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
A SHORT NOTE ON THE RELATIONSHIP BETWEEN GOAL PROGRAMMING AND FUZZY PROGRAMMING FOR
VECTORMAXIMUM PROBLEMS
M. A.
Yaghoobi
M.
Tamiz
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
2005
10
21
31
36
http://ijfs.usb.ac.ir/article_480_7b6cf03b7e38d16e82e65f5ff0221149.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
A METHOD FOR SOLVING FUZZY LINEAR SYSTEMS
Saeid
Abbasbandy
Magid
Alavi
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
2005
10
21
37
43
http://ijfs.usb.ac.ir/article_481_7287fa5649070a2665e500ffa0d779f1.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
A NEURO-FUZZY TECHNIQUE FOR DISCRIMINATION BETWEEN INTERNAL FAULTS AND MAGNETIZING INRUSH CURRENTS IN TRANSFORMERS
HASSAN
KHORASHADI-ZADEH
MOHAMMAD REZA
AGHAEBRAHIMI
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
2005
10
21
45
57
http://ijfs.usb.ac.ir/article_482_1e80e370d9421c96322a24101a56e88e.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
MEASURING SOFTWARE PROCESSES PERFORMANCE BASED ON FUZZY MULTI AGENT MEASUREMENTS
MIR ALI
SEYYEDI
MOHAMMA
TESHNEHLAB
FEREIDOON
SHAMS
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
2005
10
21
59
70
http://ijfs.usb.ac.ir/article_483_1a16c25bab856f9572c194173aa0d2ad.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
ON ANTI FUZZY IDEALS IN NEAR-RINGS
Kyung Ho
Kim
Young Bae
Jun
Yong Ho
Yon
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
2005
10
21
71
80
http://ijfs.usb.ac.ir/article_484_4fb52b20fde87511ab0820dd4e44ad02.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2005
2
2
Persian-translation vol.2, no.2 October 2005
2005
10
29
83
90
http://ijfs.usb.ac.ir/article_3124_0cb94c10119b1b62f819725b5ccefa3b.pdf