University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
Cover vol. 14, no. 3, June 2017-
0
EN
10.22111/ijfs.2017.3245
http://ijfs.usb.ac.ir/article_3245.html
http://ijfs.usb.ac.ir/article_3245_ccd98255cc13944d3522d1a0d610959a.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
ROBUST FUZZY CONTROL DESIGN USING GENETIC ALGORITHM OPTIMIZATION APPROACH: CASE STUDY OF SPARK IGNITION ENGINE TORQUE CONTROL
1
13
EN
Aris
Triwiyatno
Department of Electrical Engineering, Diponegoro University,
Semarang, Indonesia
aristriwiyatno@yahoo.com
Sumardi
Sumardi
Department of Electrical Engineering, Diponegoro University,
Semarang, Indonesia
Esa
Apriaskar
Department of Electrical Engineering, Diponegoro University, Se-
marang, Indonesia
esaindo@gmail.com
10.22111/ijfs.2017.3238
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.
Fuzzy Logic,Robust fuzzy control,Takagi-Sugeno fuzzy model,Genetic Algorithm,Engine torque control,Spark ignition engine
http://ijfs.usb.ac.ir/article_3238.html
http://ijfs.usb.ac.ir/article_3238_c398a2f414222f158d23d078724feb5f.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
TIME-VARYING FUZZY SETS BASED ON A GAUSSIAN MEMBERSHIP FUNCTIONS FOR DEVELOPING FUZZY CONTROLLER
15
39
EN
Salim
Ziani
Department of Electronics, Laboratory of Automatic and Robotics
LARC, University of Mentouri brother's Constantine, Route Ain ElBey, 25000, Constantine , Algeria
10.22111/ijfs.2017.3241
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.
Fuzzy sets,Fuzzy System,Gaussian Membership function,PDC fuzzy controller,PSO method,TS model and stability,LMI
http://ijfs.usb.ac.ir/article_3241.html
http://ijfs.usb.ac.ir/article_3241_d7be948724c863333e8a4d68ec6387ae.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
MULTI CLASS BRAIN TUMOR CLASSIFICATION OF MRI IMAGES USING HYBRID STRUCTURE DESCRIPTOR AND FUZZY LOGIC BASED RBF KERNEL SVM
41
54
EN
A.
Jayachandran
Department of CSE, PSN College of Engineering and Technology, Tirunelveli, India
R.
Dhanasekaran
Department of EEE, Syed Ammal Engineering College,
Ramanathapuram,India
10.22111/ijfs.2017.3243
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%.
MRI,Classification,Fuzzy support vector machine,Feature selection,Texture,tumor class,Radial Basics Function (RBF)
http://ijfs.usb.ac.ir/article_3243.html
http://ijfs.usb.ac.ir/article_3243_b8813791bf5849715994dda4eea36e16.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
FUZZY PREORDERED SET, FUZZY TOPOLOGY AND FUZZY AUTOMATON BASED ON GENERALIZED RESIDUATED LATTICE
55
66
EN
Anupam K.
Singh
Amity Institute of Applied Science (AIAS), Amity University,
Sector-125, Noida, Uttar Pradesh-201313, India
10.22111/ijfs.2017.3255
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.
Generalized residuated lattice,(left/right) Subsystem,Fuzzy automata,Alexandrov (left/right) fuzzy topology
http://ijfs.usb.ac.ir/article_3255.html
http://ijfs.usb.ac.ir/article_3255_201b41030e5c74457d34ff1e9b8fee44.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
A COMMON FRAMEWORK FOR LATTICE-VALUED, PROBABILISTIC AND APPROACH UNIFORM (CONVERGENCE) SPACES
67
81
EN
Gunther
Jager
School of Mechanical Engineering, University of Applied Sciences
Stralsund, 18435 Stralsund, Germany
g.jager@ru.ac.za, gunther.jaeger@fh-stralsund.de
10.22111/ijfs.2017.3256
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.
Stratified lattice-valued uniformity,Stratified lattice-valued uniform convergence space,Probabilistic uniform convergence space,Approach uniform convergence space,Stratified $LM$-filter
http://ijfs.usb.ac.ir/article_3256.html
http://ijfs.usb.ac.ir/article_3256_cfb014316ad07007c6f93e1601624252.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
GRADED DIUNIFORMITIES
83
103
EN
Ramazan
Ekmekci
Department of Mathematics, Canakkale Onsekiz Mart University,
Canakkale, TURKEY
Rza
Erturk
Department of Mathematics, Hacettepe University, Ankara, TURKEY
10.22111/ijfs.2017.3257
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.
Texture,Graded ditopology,Graded diuniformity,Fuzzy topology
http://ijfs.usb.ac.ir/article_3257.html
http://ijfs.usb.ac.ir/article_3257_dbef2e3527c8756110916bb957e71ffa.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
STABILITY OF THE JENSEN'S FUNCTIONAL EQUATION IN MULTI-FUZZY NORMED SPACES
105
119
EN
Mahnaz
Khanehgir
Department of Mathematics, Mashhad Branch, Islamic Azad University, Mashhad, Iran
mkhanehgir@gmail.com
10.22111/ijfs.2017.3258
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.
Fuzzy normed space,Ulam-Hyers stability,Jensen's functional equation,Multi-normed space
http://ijfs.usb.ac.ir/article_3258.html
http://ijfs.usb.ac.ir/article_3258_153830833c2db157f46d916f0391cc8f.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
THE CATEGORY OF T-CONVERGENCE SPACES AND ITS CARTESIAN-CLOSEDNESS
121
138
EN
Qian
Yu
Department of Mathematics, Ocean University of China, 238 Songling Road,
266100, Qingdao, P.R. China
yuqian198436@sina.com
Jinming
Fang
Department of Mathematics, Ocean University of China, 238 Songling
Road, 266100, Qingdao, P.R. China
jining-fang@163.com
10.22111/ijfs.2017.3259
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.
T-lter,T-convergence,Cartesian-closedness,Topological category,Reflection,Strong L-topology
http://ijfs.usb.ac.ir/article_3259.html
http://ijfs.usb.ac.ir/article_3259_94e21cd4aee3c5cea49d7c6e5fe6545d.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
M-FUZZIFYING MATROIDS INDUCED BY M-FUZZIFYING CLOSURE OPERATORS
139
149
EN
Xiu
Xin
Department of Mathematics, Tianjin University of Technology, Tianjin
300384, P.R.China
xinxiu518@163.com
Shao-Jun
Yang
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
shaojunyang@outlook.com
10.22111/ijfs.2017.3260
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.
M$-fuzzifying matroids,$M$-fuzzifying closure operators,$M$-fuzzifying exchange law
http://ijfs.usb.ac.ir/article_3260.html
http://ijfs.usb.ac.ir/article_3260_c77600a0362dce5dfb4eebb1a9ca369a.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
SELECTIVE GROUPOIDS AND FRAMEWORKS INDUCED BY FUZZY SUBSETS
151
160
EN
Young Hee
Kim
Department of Mathematics, Chungbuk National University, Cheongju, 28644, Korea
yhkim@cbnu.ac.kr
Hee Sik
Kim
Research Institute for Natural Sci., Department of Mathematics,
Hanyang University, Seoul, 04763, Korea
heekim@hanyang.ac.kr
J.
Neggers
Department of Mathematics, University of Alabama, Tuscaloosa, AL
35487-0350, U. S. A.
jneggers@gp.as.ua.edu
10.22111/ijfs.2017.3261
In this paper, we show that every selective groupoid induced by a fuzzy subset is a pogroupoid, and we discuss several properties in quasi ordered sets by introducing the notion of a framework.
Fuzzy subset,$d/BCK$-algebra,Framework,Selective groupoid,Pogroupoid,Poset
http://ijfs.usb.ac.ir/article_3261.html
http://ijfs.usb.ac.ir/article_3261_e912d237a9797afc81f6aa643e22f9db.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
SOME FIXED POINT RESULTS FOR ADMISSIBLE GERAGHTY CONTRACTION TYPE MAPPINGS IN FUZZY METRIC SPACES
161
177
EN
Mina
Dinarvand
Faculty of Mathematics, K. N. Toosi University of Technology,
P.O. Box 16315-1618, Tehran, Iran
dinarvand_mina@yahoo.com
10.22111/ijfs.2017.3262
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.
Fixed point,Fuzzy $alpha$-Geraghty contraction type mapping,Fuzzy $beta$-$varphi$-contractive mapping,Fuzzy metric space,Non-Archimedean fuzzy metric space
http://ijfs.usb.ac.ir/article_3262.html
http://ijfs.usb.ac.ir/article_3262_f21105381489fdc273ef65cfa66c1548.pdf
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
14
3
2017
06
29
Persian-translation vol. 14, no. 3, June 2017
181
191
EN
10.22111/ijfs.2017.3263
http://ijfs.usb.ac.ir/article_3263.html
http://ijfs.usb.ac.ir/article_3263_dd93562fdd7ac72a7841f57bf2be49ec.pdf