2018-02-25T17:07:01Z
http://ijfs.usb.ac.ir/?_action=export&rf=summon&issue=74
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
Cover Vol.4, No.1 April 2007
2007
04
30
0
http://ijfs.usb.ac.ir/article_2910_2e784435556c4da339b26e553e994ebf.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
DISTRIBUTED AND COLLABORATIVE FUZZY MODELING
WITOLD
PEDRYCZ
In this study, we introduce and study a concept of distributed fuzzymodeling. Fuzzy modeling encountered so far is predominantly of a centralizednature by being focused on the use of a single data set. In contrast to this style ofmodeling, the proposed paradigm of distributed and collaborative modeling isconcerned with distributed models which are constructed in a highly collaborativefashion. In a nutshell, distributed models reconcile and aggregate findings of theindividual fuzzy models produced on a basis of local data sets. The individualmodels are formed in a highly synergistic, collaborative manner. Given the fact thatfuzzy models are inherently granular constructs that dwell upon collections ofinformation granules – fuzzy sets, this observation implies a certain generaldevelopment process. There are two fundamental design issues of this style ofmodeling, namely (a) a formation of information granules carried out on a basis oflocally available data and their collaborative refinement, and (b) construction oflocal models with the use of properly established collaborative linkages. We discussthe underlying general concepts and then elaborate on their detailed development.Information granulation is realized in terms of fuzzy clustering. Local modelsemerge in the form of rule-based systems. The paper elaborates on a number ofmechanisms of collaboration offering two general categories of so-calledhorizontal and vertical clustering. The study also addresses an issue ofcollaboration in cases when such interaction involves information granules formedat different levels of specificity (granularity). It is shown how various algorithms ofcollaboration lead to the emergence of fuzzy models involving informationgranules of higher type such as e.g., type-2 fuzzy sets.
Computational Intelligence
C^{3} paradigm
Distributed processing
Fuzzy
clustering
Fuzzy models
2007
04
09
1
19
http://ijfs.usb.ac.ir/article_353_e16a2e92cedec4f2fbb09d7c81a6cb72.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
USING DISTRIBUTION OF DATA TO ENHANCE PERFORMANCE OF FUZZY CLASSIFICATION SYSTEMS
EGHBAL G.
MANSOORI
MANSOOR J.
ZOLGHADRI
SERAJ D.
KATEBI
This paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. The classification performance andinterpretability are of major importance in these systems. In this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). Ourapproach uses a punishment algorithm to reduce the decision subspace of a ruleby reducing its weight, such that its performance is enhanced. Obviously, thisreduction will cause the decision subspace of adjacent overlapping rules to beincreased and consequently rewarding these rules. The results of computersimulations on some well-known data sets show the effectiveness of ourapproach.
Fuzzy rule-based classification systems
Rule weight
2007
04
09
21
36
http://ijfs.usb.ac.ir/article_355_8012934623da6f85204a71c666c34242.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
FUZZY BASED FAULT DETECTION AND CONTROL FOR 6/4 SWITCHED RELUCTANCE MOTOR
N.
SELVAGANESAN
D.
RAJA
S.
SRINIVASAN
Prompt detection and diagnosis of faults in industrial systems areessential to minimize the production losses, increase the safety of the operatorand the equipment. Several techniques are available in the literature to achievethese objectives. This paper presents fuzzy based control and fault detection for a6/4 switched reluctance motor. The fuzzy logic control performs like a classicalproportional plus integral control, giving the current reference variation based onspeed error and its change. Also, the fuzzy inference system is created and rulebase are evaluated relating the parameters to the type of the faults. These rules arefired for specific changes in system parameters and the faults are diagnosed. Thefeasibility of fuzzy based fault diagnosis and control scheme is demonstrated byapplying it to a simulated system.
Fault Diagnosis
Fuzzy Logic
Switched Reluctance Motor
Fuzzy
Inference Systems
2007
04
09
37
51
http://ijfs.usb.ac.ir/article_356_9057931d5fc7d9338fab8be76e173fb2.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
SOME RESULTS ON INTUITIONISTIC FUZZY SPACES
S. B.
Hosseini
Donal
O’Regan
Reza
Saadati
In this paper we define intuitionistic fuzzy metric and normedspaces. We first consider finite dimensional intuitionistic fuzzy normed spacesand prove several theorems about completeness, compactness and weak convergencein these spaces. In section 3 we define the intuitionistic fuzzy quotientnorm and study completeness and review some fundamental theorems. Finally,we consider some properties of approximation theory in intuitionistic fuzzymetric spaces.
Intuitionistic fuzzy metric (normed) spaces
Completeness
Compactness
Finite dimensional
Weak convergence
Quotient spaces
Approximation theory
2007
04
09
53
64
http://ijfs.usb.ac.ir/article_357_3141e238301eb28b17f345772521dbda.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
L-FUZZY BILINEAR OPERATOR AND ITS CONTINUITY
Cong-hua
Yan
Jin-xuan
Fang
The purpose of this paper is to introduce the concept of L-fuzzybilinear operators. We obtain a decomposition theorem for L-fuzzy bilinearoperators and then prove that a L-fuzzy bilinear operator is the same as apowerset operator for the variable-basis introduced by S.E.Rodabaugh (1991).Finally we discuss the continuity of L-fuzzy bilinear operators.
Order-homomorphism
Powerset operator
L-bilinear operator
Molecule
net
2007
04
09
65
73
http://ijfs.usb.ac.ir/article_358_af8602c55b74198bfce9a442e63cec84.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
TRIANGULAR FUZZY MATRICES
Amiya Kumar l
Shyama
Madhumangal
Pal
In this paper, some elementary operations on triangular fuzzynumbers (TFNs) are defined. We also define some operations on triangularfuzzy matrices (TFMs) such as trace and triangular fuzzy determinant(TFD). Using elementary operations, some important properties of TFMs arepresented. The concept of adjoints on TFM is discussed and some of theirproperties are. Some special types of TFMs (e.g. pure and fuzzy triangular,symmetric, pure and fuzzy skew-symmetric, singular, semi-singular, constant)are defined and a number of properties of these TFMs are presented.
Triangular fuzzy numbers
Triangular fuzzy number arithmetic
Triangular
fuzzy matrices
Triangular fuzzy determinant
2007
04
09
75
87
http://ijfs.usb.ac.ir/article_359_0038d4fb0f550de224041cbbbd77caf6.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
INTUITIONISTIC FUZZY BOUNDED LINEAR OPERATORS
S.
Vijayabalaji
N.
Thillaigovindan
The object of this paper is to introduce the notion of intuitionisticfuzzy continuous mappings and intuitionistic fuzzy bounded linear operatorsfrom one intuitionistic fuzzy n-normed linear space to another. Relation betweenintuitionistic fuzzy continuity and intuitionistic fuzzy bounded linearoperators are studied and some interesting results are obtained.
fuzzy n-norm
intuitionistic fuzzy n-norm
intuitionistic fuzzy continuous
mapping
intuitionistic fuzzy bounded linear operator
2007
04
09
89
101
http://ijfs.usb.ac.ir/article_361_9c78a3a61bf8f44f026f0d019b06cef9.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2007
4
1
Persian-translation Vol.4, No.1 April 2007
2007
04
30
105
111
http://ijfs.usb.ac.ir/article_2911_64fd55c1f871dba2e12a5205e4b5b3d1.pdf