eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
0
10.22111/ijfs.2017.3245
3245
Cover vol. 14, no. 3, June 2017-
http://ijfs.usb.ac.ir/article_3245_ccd98255cc13944d3522d1a0d610959a.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
1
13
10.22111/ijfs.2017.3238
3238
مقاله پژوهشی
ROBUST FUZZY CONTROL DESIGN USING GENETIC ALGORITHM OPTIMIZATION APPROACH: CASE STUDY OF SPARK IGNITION ENGINE TORQUE CONTROL
Aris Triwiyatno
aristriwiyatno@yahoo.com
1
Sumardi Sumardi
2
Esa Apriaskar
esaindo@gmail.com
3
Department of Electrical Engineering, Diponegoro University, Semarang, Indonesia
Department of Electrical Engineering, Diponegoro University, Semarang, Indonesia
Department of Electrical Engineering, Diponegoro University, Se- marang, Indonesia
In the case of widely-uncertain non-linear system control design, it was very difficult to design a single controller to overcome control design specifications in all of its dynamical characteristics uncertainties. To resolve these problems, a new design method of robust fuzzy control proposed. The solution offered was by creating multiple soft-switching with Takagi-Sugeno fuzzy model for optimal solution control at all operating points that generate uncertainties. Optimal solution control at each operating point was calculated using genetic algorithm. A case study of engine torque control of spark ignition engine model was used to prove this new method of robust fuzzy control design. From the simulation results, it can be concluded that the controller operates very well for a wide uncertainty.
http://ijfs.usb.ac.ir/article_3238_c398a2f414222f158d23d078724feb5f.pdf
Fuzzy Logic
Robust fuzzy control
Takagi-Sugeno fuzzy model
Genetic Algorithm
Engine torque control
Spark ignition engine
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
15
39
10.22111/ijfs.2017.3241
3241
مقاله پژوهشی
TIME-VARYING FUZZY SETS BASED ON A GAUSSIAN MEMBERSHIP FUNCTIONS FOR DEVELOPING FUZZY CONTROLLER
Salim Ziani
1
Department of Electronics, Laboratory of Automatic and Robotics LARC, University of Mentouri brother's Constantine, Route Ain ElBey, 25000, Constantine , Algeria
The paper presents a novel type of fuzzy sets, called time-Varying Fuzzy Sets (VFS). These fuzzy sets are based on the Gaussian membership functions, they are depended on the error and they are characterized by the displacement of the kernels to both right and left side of the universe of discourse, the two extremes kernels of the universe are fixed for all time. In this work we focus only on the midpoint movement of the universe, all points of supports (kernels) are shifted by the same distance and in the same direction excepted the two extremes points of supports are always fixed for all computation time. To show the effectiveness of this approach we used these VFS to develop a PDC (Parallel Distributed Compensation) fuzzy controller for a nonlinear and certain system in continuous time described by the T-S fuzzy model, the parameters of the functions defining the midpoint movements are optimized by a PSO (Particle Swarm Optimization) approach.
http://ijfs.usb.ac.ir/article_3241_d7be948724c863333e8a4d68ec6387ae.pdf
Fuzzy sets
Fuzzy System
Gaussian Membership function
PDC fuzzy controller
PSO method
TS model and stability
LMI
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
41
54
10.22111/ijfs.2017.3243
3243
مقاله پژوهشی
MULTI CLASS BRAIN TUMOR CLASSIFICATION OF MRI IMAGES USING HYBRID STRUCTURE DESCRIPTOR AND FUZZY LOGIC BASED RBF KERNEL SVM
A. Jayachandran
1
R. Dhanasekaran
2
Department of CSE, PSN College of Engineering and Technology, Tirunelveli, India
Department of EEE, Syed Ammal Engineering College, Ramanathapuram,India
Medical Image segmentation is to partition the image into a set of regions that are visually obvious and consistent with respect to some properties such as gray level, texture or color. Brain tumor classification is an imperative and difficult task in cancer radiotherapy. The objective of this research is to examine the use of pattern classification methods for distinguishing different types of brain tumors, such as primary gliomas from metastases, and also for grading of gliomas. Manual classification results look better because it involves human intelligence but the disadvantage is that the results may differ from one person to another person and takes long time. MRI image based automatic diagnosis method is used for early diagnosis and treatment of brain tumors. In this article, fully automatic, multi class brain tumor classification approach using hybrid structure descriptor and Fuzzy logic based Pair of RBF kernel support vector machine is developed. The method was applied to a population of 102 brain tumors histologically diagnosed as Meningioma (115), Metastasis (120), Gliomas grade II (65) and Gliomas grade II (70). Classification accuracy of proposed system in class 1(Meningioma) type tumor is 98.6%, class 2 (Metastasis) is 99.29%, class 3(Gliomas grade II) is 97.87% and class 4(Gliomas grade III) is 98.6%.
http://ijfs.usb.ac.ir/article_3243_b8813791bf5849715994dda4eea36e16.pdf
MRI
Classification
Fuzzy support vector machine
Feature selection
Texture
tumor class
Radial Basics Function (RBF)
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
55
66
10.22111/ijfs.2017.3255
3255
مقاله پژوهشی
FUZZY PREORDERED SET, FUZZY TOPOLOGY AND FUZZY AUTOMATON BASED ON GENERALIZED RESIDUATED LATTICE
Anupam K. Singh
1
Amity Institute of Applied Science (AIAS), Amity University, Sector-125, Noida, Uttar Pradesh-201313, India
This work is towards the study of the relationship between fuzzy preordered sets and Alexandrov (left/right) fuzzy topologies based on generalized residuated lattices here the fuzzy sets are equipped with generalized residuated lattice in which the commutative property doesn't hold. Further, the obtained results are used in the study of fuzzy automata theory.
http://ijfs.usb.ac.ir/article_3255_201b41030e5c74457d34ff1e9b8fee44.pdf
Generalized residuated lattice
(left/right) Subsystem
Fuzzy automata
Alexandrov (left/right) fuzzy topology
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
67
81
10.22111/ijfs.2017.3256
3256
مقاله پژوهشی
A COMMON FRAMEWORK FOR LATTICE-VALUED, PROBABILISTIC AND APPROACH UNIFORM (CONVERGENCE) SPACES
Gunther Jager
g.jager@ru.ac.za, gunther.jaeger@fh-stralsund.de
1
School of Mechanical Engineering, University of Applied Sciences Stralsund, 18435 Stralsund, Germany
We develop a general framework for various lattice-valued, probabilistic and approach uniform convergence spaces. To this end, we use the concept of $s$-stratified $LM$-filter, where $L$ and $M$ are suitable frames. A stratified $LMN$-uniform convergence tower is then a family of structures indexed by a quantale $N$. For different choices of $L,M$ and $N$ we obtain the lattice-valued, probabilistic and approach uniform convergence spaces as examples. We show that the resulting category $sLMN$-$UCTS$ is topological, well-fibred and Cartesian closed. We furthermore define stratified $LMN$-uniform tower spaces and show that the category of these spaces is isomorphic to the subcategory of stratified $LMN$-principal uniform convergence tower spaces. Finally we study the underlying stratified $LMN$-convergence tower spaces.
http://ijfs.usb.ac.ir/article_3256_cfb014316ad07007c6f93e1601624252.pdf
Stratified lattice-valued uniformity
Stratified lattice-valued uniform convergence space
Probabilistic uniform convergence space
Approach uniform convergence space
Stratified $LM$-filter
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
83
103
10.22111/ijfs.2017.3257
3257
مقاله پژوهشی
GRADED DIUNIFORMITIES
Ramazan Ekmekci
1
Rza Erturk
2
Department of Mathematics, Canakkale Onsekiz Mart University, Canakkale, TURKEY
Department of Mathematics, Hacettepe University, Ankara, TURKEY
Graded ditopological texture spaces have been presented and discussed in categorical aspects by Lawrence M. Brown and Alexander {v S}ostak in cite{BS}. In this paper, the authors generalize the structure of diuniformity in ditopological texture spaces defined in cite{OB} to the graded ditopological texture spaces and investigate graded ditopologies generated by graded diuniformities. The autors also compare the properties of diuniformities and graded diuniformities.
http://ijfs.usb.ac.ir/article_3257_dbef2e3527c8756110916bb957e71ffa.pdf
Texture
Graded ditopology
Graded diuniformity
Fuzzy topology
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
105
119
10.22111/ijfs.2017.3258
3258
مقاله پژوهشی
STABILITY OF THE JENSEN'S FUNCTIONAL EQUATION IN MULTI-FUZZY NORMED SPACES
Mahnaz Khanehgir
mkhanehgir@gmail.com
1
Department of Mathematics, Mashhad Branch, Islamic Azad University, Mashhad, Iran
In this paper, we define the notion of (dual) multi-fuzzy normedspaces and describe some properties of them. We then investigate Ulam-Hyers stability of Jensen's functional equation for mappings from linear spaces into multi-fuzzy normed spaces. We establish an asymptotic behavior of the Jensen equation in the framework of multi-fuzzy normed spaces.
http://ijfs.usb.ac.ir/article_3258_153830833c2db157f46d916f0391cc8f.pdf
Fuzzy normed space
Ulam-Hyers stability
Jensen's functional equation
Multi-normed space
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
121
138
10.22111/ijfs.2017.3259
3259
مقاله پژوهشی
THE CATEGORY OF T-CONVERGENCE SPACES AND ITS CARTESIAN-CLOSEDNESS
Qian Yu
yuqian198436@sina.com
1
Jinming Fang
jining-fang@163.com
2
Department of Mathematics, Ocean University of China, 238 Songling Road, 266100, Qingdao, P.R. China
Department of Mathematics, Ocean University of China, 238 Songling Road, 266100, Qingdao, P.R. China
In this paper, we define a kind of lattice-valued convergence spaces based on the notion of $top$-filters, namely $top$-convergence spaces, and show the category of $top$-convergence spaces is Cartesian-closed. Further, in the lattice valued context of a complete $MV$-algebra, a close relation between the category of$top$-convergence spaces and that of strong $L$-topological spaces is established. In details, we show that the category of strong $L$-topological spaces is concretely isomorphic to that of strong $L$-topological $top$-convergence spaces categorically and bireflectively embedded in that of $top$-convergence spaces.
http://ijfs.usb.ac.ir/article_3259_94e21cd4aee3c5cea49d7c6e5fe6545d.pdf
T-lter
T-convergence
Cartesian-closedness
Topological category
Reflection
Strong L-topology
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
139
149
10.22111/ijfs.2017.3260
3260
مقاله پژوهشی
M-FUZZIFYING MATROIDS INDUCED BY M-FUZZIFYING CLOSURE OPERATORS
Xiu Xin
xinxiu518@163.com
1
Shao-Jun Yang
shaojunyang@outlook.com
2
Department of Mathematics, Tianjin University of Technology, Tianjin 300384, P.R.China
School of Mathematics and Statistics, Beijing Institute of Tech- nology, Beijing 100081, P.R.China and Beijing Key Laboratory on MCAACI, Beijing Institute of Technology, Beijing 100081, P.R.China
In this paper, the notion of closure operators of matroids is generalized to fuzzy setting which is called $M$-fuzzifying closure operators, and some properties of $M$-fuzzifying closure operators are discussed. The $M$-fuzzifying matroid induced by an $M$-fuzzifying closure operator can induce an $M$-fuzzifying closure operator. Finally, the characterizations of $M$-fuzzifying acyclic matroids are given.
http://ijfs.usb.ac.ir/article_3260_c77600a0362dce5dfb4eebb1a9ca369a.pdf
M$-fuzzifying matroids
$M$-fuzzifying closure operators
$M$-fuzzifying exchange law
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
151
160
10.22111/ijfs.2017.3261
3261
مقاله پژوهشی
SELECTIVE GROUPOIDS AND FRAMEWORKS INDUCED BY FUZZY SUBSETS
Young Hee Kim
yhkim@cbnu.ac.kr
1
Hee Sik Kim
heekim@hanyang.ac.kr
2
J. Neggers
jneggers@gp.as.ua.edu
3
Department of Mathematics, Chungbuk National University, Cheongju, 28644, Korea
Research Institute for Natural Sci., Department of Mathematics, Hanyang University, Seoul, 04763, Korea
Department of Mathematics, University of Alabama, Tuscaloosa, AL 35487-0350, U. S. A.
In this paper, we show that every selective groupoid induced by a fuzzy subset is a pogroupoid, and we discuss several properties in quasi ordered sets by introducing the notion of a framework.
http://ijfs.usb.ac.ir/article_3261_e912d237a9797afc81f6aa643e22f9db.pdf
Fuzzy subset
$d/BCK$-algebra
Framework
Selective groupoid
Pogroupoid
Poset
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
161
177
10.22111/ijfs.2017.3262
3262
مقاله پژوهشی
SOME FIXED POINT RESULTS FOR ADMISSIBLE GERAGHTY CONTRACTION TYPE MAPPINGS IN FUZZY METRIC SPACES
Mina Dinarvand
dinarvand_mina@yahoo.com
1
Faculty of Mathematics, K. N. Toosi University of Technology, P.O. Box 16315-1618, Tehran, Iran
In this paper, we introduce the notions of fuzzy $alpha$-Geraghty contraction type mapping and fuzzy $beta$-$varphi$-contractive mapping and establish some interesting results on the existence and uniqueness of fixed points for these two types of mappings in the setting of fuzzy metric spaces and non-Archimedean fuzzy metric spaces. The main results of our work generalize and extend some known comparable results in the literature. Furthermore, several illustrative examples are given to support the usability of our obtained results.
http://ijfs.usb.ac.ir/article_3262_f21105381489fdc273ef65cfa66c1548.pdf
Fixed point
Fuzzy $alpha$-Geraghty contraction type mapping
Fuzzy $beta$-$varphi$-contractive mapping
Fuzzy metric space
Non-Archimedean fuzzy metric space
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-06-29
14
3
181
191
10.22111/ijfs.2017.3263
3263
مقاله پژوهشی
Persian-translation vol. 14, no. 3, June 2017
http://ijfs.usb.ac.ir/article_3263_dd93562fdd7ac72a7841f57bf2be49ec.pdf