eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-03-01
14
1
0
10.22111/ijfs.2017.3088
3088
Cover vol. 14, no. 1, February 2017
http://ijfs.usb.ac.ir/article_3088_dd2a325fd028a1ecba3efff967ef6955.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
1
21
10.22111/ijfs.2017.3034
3034
مقاله پژوهشی
Group Generalized Interval-valued Intuitionistic Fuzzy Soft Sets and Their Applications in\ Decision Making
Hua Wu
sunshinesmilewh@gmail.com
1
Xiuqin Su
suxiuqin@opt.ac.cn
2
Key Laboratory of Ultrafast Photoelectric Diagnostics Technology, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an, China and University of Chinese Academy of Sciences, Beijing, China.
Key Laboratory of Ultrafast Photoelectric Diagnostics Technology, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an, China
Interval-valued intuitionistic fuzzy sets (IVIFSs) are widely used to handle uncertainty and imprecision in decision making. However, in more complicated environment, it is difficult to express the uncertain information by an IVIFS with considering the decision-making preference. Hence, this paper proposes a group generalized interval-valued intuitionistic fuzzy soft set (G-GIVIFSS) which contains the basic description by interval-valued intuitionistic fuzzy soft set (IVIFSS) on the alternatives and a group of experts' evaluation of it. It contributes the following threefold: 1) A generalized interval-valued intuitionistic fuzzy soft set (GIVIFSS) is proposed by introducing an interval-valued intuitionistic fuzzy parameter, which reflects a new and senior expert's opinion on the basic description. The operations, properties and aggregation operators of GIVIFSS are discussed. 2) Based on GIVIFSS, a G-GIVIFSS is then proposed to reduce the impact of decision-making preference by introducing more parameters by a group of experts. Its important operations, properties and the weighted averaging operator are also defined. 3) A multi-attribute group decision making model based on G-GIVIFSS weighted averaging operator is built to solve the group decision making problems in the more universal IVIF environment, and two practical examples are taken to validate the efficiency and effectiveness of the proposed model.
http://ijfs.usb.ac.ir/article_3034_c764374b831ad45afb14a759482b14ed.pdf
Group decision making
Interval-valued intuitionistic fuzzy set
Generalized interval-valued intuitionistic fuzzy soft set
Soft set
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
23
41
10.22111/ijfs.2017.3035
3035
مقاله پژوهشی
Soft Computing Based on a Modified MCDM Approach under Intuitionistic Fuzzy Sets
M. R. Shahriari
1
Faculty of Management, South Tehran Branch, Islamic Azad University, Tehran, Iran
The current study set to extend a new VIKOR method as a compromise ranking approach to solve multiple criteria decision-making (MCDM) problems through intuitionistic fuzzy analysis. Using compromise method in MCDM problems contributes to the selection of an alternative as close as possible to the positive ideal solution and far away from the negative ideal solution, concurrently. Using Atanassov intuitionistic fuzzy sets (A-IFSs) may simultaneously express the degree of membership and non-membership to decision makers (DMs) to describe uncertain situations in decision-making problems. The proposed intuitionistic fuzzy VIKOR indicates the degree of satisfaction and dissatisfaction of each alternative with respect to each criterion and the relative importance of each criterion, respectively, by degrees of membership and non-membership. Thus, the ratings for the importance of criteria, DMs, and alternatives are in linguistic variables and expressed in intuitionistic fuzzy numbers. Using IFS aggregation operators and with respect to subjective judgment and objective information, the most suitable alternative is indicated among potential alternatives. Moreover, practical examples illustrate the procedure of the proposed method.
http://ijfs.usb.ac.ir/article_3035_56c511a22322a3f72ffb46e35bb130df.pdf
Multiple criteria decision making (MCDM)
Decision makers (DMs)
Atanassov intuitionistic fuzzy sets (A-IFSs)
Intuitionistic fuzzy numbers
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
43
60
10.22111/ijfs.2017.3036
3036
مقاله پژوهشی
Support vector regression with random output variable and probabilistic constraints
Maryam Abaszade
1
Sohrab Effati
s-effati.profcms@um.ac.ir
2
Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran
Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran
Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadratic optimization problem. The proposedmethod is illustrated by several simulated data and real data sets for both models (linear and nonlinear) with probabilistic constraints.
http://ijfs.usb.ac.ir/article_3036_7fa269af1f035bda8d625aada763cf7a.pdf
Probabilistic constraints
Support Vector Machine
Support Vector Regression
Quadratic programming
Probability function
Monte Carlo simulation
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
61
75
10.22111/ijfs.2017.3037
3037
مقاله پژوهشی
A Tauberian theorem for $(C,1,1)$ summable double sequences of fuzzy numbers
Ibrahim Canak
ibrahimcanak@yahoo.com
1
Umit Totur
utotur@adu.edu.tr
2
Zerrin Onder
zerrin.onder11@gmail.com
3
Department of Mathematics, Ege University, 35100, Izmir, Turkey
Department of Mathematics, Adnan Menderes University, 09100, Aydin, Turkey
Department of Mathematics, Ege University, 35100, Izmir, Turkey
In this paper, we determine necessary and sufficient Tauberian conditions under which convergence in Pringsheim's sense of a double sequence of fuzzy numbers follows from its $(C,1,1)$ summability. These conditions are satisfied if the double sequence of fuzzy numbers is slowly oscillating in different senses. We also construct some interesting double sequences of fuzzy numbers.
http://ijfs.usb.ac.ir/article_3037_e93bbd0f6b9452e82d1a57a8403f41d7.pdf
Fuzzy numbers
Double sequences
Slow oscillation
Summability $(C
1
1)$
Tauberian theorems
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
77
87
10.22111/ijfs.2017.3038
3038
مقاله پژوهشی
Some topological properties of spectrum of fuzzy submodules
R. Ameri
rez_ameri@yahoo.com
1
R. Mahjoob
ra−mahjoob@yahoo.com
2
School of Mathematics, Statistics and Computer Science, College of Sciences, University of Tehran, Teheran, Iran
Department of Mathematics, Semnan University, Semnan, Iran
Let $R$ be a commutative ring with identity and $M$ be an$R$-module. Let $FSpec(M)$ denotes the collection of all prime fuzzysubmodules of $M$. In this regards some basic properties of Zariskitopology on $FSpec(M)$ are investigated. In particular, we provesome equivalent conditions for irreducible subsets of thistopological space and it is shown under certain conditions$FSpec(M)$ is a $T_0-$space or Hausdorff.
http://ijfs.usb.ac.ir/article_3038_cf0537ee7303573d6949705f2d57737a.pdf
Fuzzy prime submodule
Fuzzy prime spectrum
Zariski topology
Irreducible subset
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
89
97
10.22111/ijfs.2017.3041
3041
مقاله پژوهشی
ON LOCAL HUDETZ g-ENTROPY
M. Rahimi
m10.rahimi@gmail.com
1
Department of Mathematics, Faculty of Science, University of Qom, Qom, Iran
In this paper, a local approach to the concept of Hudetz $g$-entropy is presented. The introduced concept is stated in terms of Hudetz $g$-entropy. This representation is based on the concept of $g$-ergodic decomposition which is a result of the Choquet's representation Theorem for compact convex metrizable subsets of locally convex spaces.
http://ijfs.usb.ac.ir/article_3041_ca853dd5bb21099ad707b1cc56ee9624.pdf
$g$-entropy
$g$-ergodic decomposision
Hudetz correction
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
99
113
10.22111/ijfs.2017.3045
3045
مقاله پژوهشی
Probabilistic Normed Groups
Kourosh Nourouzi
nourouzi@kntu.ac.ir
1
Alireza Pourmoslemi
a_pourmoslemy@pnu.ac.ir
2
Faculty of Mathematics, K.N.Toosi University of Technology, P.O.Box 16315-1618, Tehran, Iran.
Department of Mathematics, Payame Noor University, P.O.BOX 19395-3697, Tehran, Iran.
In this paper, we introduce the probabilistic normed groups. Among other results, we investigate the continuityof inner automorphisms of a group and the continuity of left and right shifts in probabilistic group-norm. We also study midconvex functions defined on probabilistic normed groups and give some results about locally boundedness of such functions.
http://ijfs.usb.ac.ir/article_3045_07ffef6232373ba99af3aa077fbf129e.pdf
Probabilistic normed groups
Invariant probabilistic metrics
Distributional-slowly varying functions
Midconvex functions
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
115
130
10.22111/ijfs.2017.3046
3046
مقاله پژوهشی
Implications, coimplications and left semi-uninorms on a complete lattice
Yuan Wang
yctuwangyuan@163.com
1
Keming Tang
tkmchina@126.com
2
Zhudeng Wang
zhudengwang2004@163.com
3
College of Information Engineering, Yancheng Teachers University, Jiangsu 224002, People's Republic of China
College of Information Engineering, Yancheng Teachers University, Jiangsu 224002, People's Republic of China
School of Mathematics and Statistics, Yancheng Teachers University, Jiangsu 224002, People's Republic of China
In this paper, we firstly show that the $N$-dual operation of the right residual implication, which is induced by a left-conjunctive right arbitrary $vee$-distributive left semi-uninorm, is the right residual coimplication induced by its $N$-dual operation. As a dual result, the $N$-dual operation of the right residual coimplication, which is induced by a left-disjunctive right arbitrary $wedge$-distributive left semi-uninorm, is the right residual implication induced by its $N$-dual operation. Then, we demonstrate that the $N$-dual operations of the left semi-uninorms induced by an implication and a coimplication, which satisfy the neutrality principle, are the left semi-uninorms. Finally, we reveal the relationships between conjunctive right arbitrary $vee$-distributive left semi-uninorms induced by implications and disjunctive right arbitrary $wedge$-distributive left semi-uninorms induced by coimplications, where both implications and coimplications satisfy the neutrality principle.
http://ijfs.usb.ac.ir/article_3046_01bd93593faf02d51d0a59def6a543fe.pdf
Fuzzy connective
Implication
Coimplication
Left semi-uninorm
Neutrality principle
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
131
144
10.22111/ijfs.2017.3048
3048
مقاله پژوهشی
Structural properties of fuzzy graphs
Xiaonan Li
xnli@xidian.edu.cn
1
Huangjian Yi
yhj255@163.com
2
School of Mathematics and Statistics, Xidian University, Xi'an, 710071, Shaanxi, China
School of Information and Technology, Northwest University, Xi'an, 710069, Shaanxi, China
Matroids are important combinatorial structures and connect close-lywith graphs. Matroids and graphs were all generalized to fuzzysetting respectively. This paper tries to study connections betweenfuzzy matroids and fuzzy graphs. For a given fuzzy graph, we firstinduce a sequence of matroids from a sequence of crisp graph, i.e.,cuts of the fuzzy graph. A fuzzy matroid, named graph fuzzy matroid,is then constructed by using the sequence of matroids. An equivalentdescription of graphic fuzzy matroids is given and their propertiesof fuzzy bases and fuzzy circuits are studied.
http://ijfs.usb.ac.ir/article_3048_b36fae2bb90f788b2a7a140802ec8baa.pdf
Fuzzy graph
Partial fuzzy subgraph
Cycle
Fuzzy matroid
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
145
162
10.22111/ijfs.2017.3050
3050
مقاله پژوهشی
M-FUZZIFYING INTERVAL SPACES
Zhen-Yu Xiu
xyz198202@163.com
1
Fu-Gui Shi
fugushi@bit.edu.cn
2
College of Applied Mathematics, Chengdu University of Information Technology, Chengdu 610000, P.R. China
chool of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, P.R. China
In this paper, we introduce the notion of $M$-fuzzifying interval spaces, and discuss the relationship between $M$-fuzzifying interval spaces and $M$-fuzzifying convex structures.It is proved that the category {bf MYCSA2} can be embedded in the category {bf MYIS} as a reflective subcategory, where {bf MYCSA2} and {bf MYIS} denote the category of $M$-fuzzifying convex structures of $M$-fuzzifying arity $leq 2$ and the category of $M$-fuzzifying interval spaces, respectively. Under the framework of $M$-fuzzifying interval spaces, subspaces and product spaces are presented and some of their fundamental properties are obtained.
http://ijfs.usb.ac.ir/article_3050_199fd4b0125cf88df6ef7f1e2066dd5c.pdf
$M$-fuzzifying interval spaces
$M$-fuzzifying convex structures
$M$-fuzzifying interval preserving functions
Subspaces
Product spaces
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-02-28
14
1
163
181
10.22111/ijfs.2017.3051
3051
مقاله پژوهشی
COUNTING DISTINCT FUZZY SUBGROUPS OF SOME RANK-3 ABELIAN GROUPS
Isaac K. Appiah
1
B. B. Makamba
bbmakamba@ufh.ac.za
2
Department of Mathematics, University of Fort Hare, ALICE, 5700, South Africa
Department of Mathematics, University of Fort Hare, ALICE, 5700, South Africa
In this paper we classify fuzzy subgroups of a rank-3 abelian group $G = mathbb{Z}_{p^n} + mathbb{Z}_p + mathbb{Z}_p$ for any fixed prime $p$ and any positive integer $n$, using a natural equivalence relation given in cite{mur:01}. We present and prove explicit polynomial formulae for the number of (i) subgroups, (ii) maximal chains of subgroups, (iii) distinct fuzzy subgroups, (iv) non-isomorphic maximal chains of subgroups and (v) classes of isomorphic fuzzy subgroups of $G$. Illustrative examples are provided.
http://ijfs.usb.ac.ir/article_3051_d9c53364056080d2ad2e5d2af478926e.pdf
Equivalence
Fuzzy subgroup
Maximal chain
Keychain
Distinguishing factor
Isomorphism
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-03-01
14
1
185
195
10.22111/ijfs.2017.3089
3089
Persian-translation vol. 14, no. 1, February 2017
http://ijfs.usb.ac.ir/article_3089_96891c6b02f1f2f16c91eec6e6a77e02.pdf