eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-01
14
6
0
10.22111/ijfs.2017.3504
3504
Cover vol. 14, no. 6, December 2017
http://ijfs.usb.ac.ir/article_3504_e75c3dcf8c1fe24b35436246ee473aff.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
1
13
10.22111/ijfs.2017.3495
3495
مقاله پژوهشی
F-TRANSFORM FOR NUMERICAL SOLUTION OF TWO-POINT BOUNDARY VALUE PROBLEM
Irina Perfilieva
irina.perfilieva@osu.cz
1
Petra Stevuliakova
2
Radek Valasek
3
University of Ostrava, Centre of Excellence IT4Innovations, Institute for Research and Applications of Fuzzy Modeling, 30. dubna 22, 701 03 Ostrava 1, Czech Republic
University of Ostrava, Centre of Excellence IT4Innovations, Institute for Research and Applications of Fuzzy Modeling, 30. dubna 22, 701 03 Ostrava 1, Czech Republic
University of Ostrava, Centre of Excellence IT4Innovations, Institute for Research and Applications of Fuzzy Modeling, 30. dubna 22, 701 03 Ostrava 1, Czech Republic
We propose a fuzzy-based approach aiming at finding numerical solutions to some classical problems. We use the technique of F-transform to solve a second-order ordinary differential equation with boundary conditions. We reduce the problem to a system of linear equations and make experiments that demonstrate applicability of the proposed method. We estimate the order of accuracy of the proposed method. We show that the F-transform-based approach does not only extend the set of its applications, but has a certain advantage in the solution of ill-posed problems.
http://ijfs.usb.ac.ir/article_3495_ccab4ef5ff4c62aba8a2fe33db1a5b8e.pdf
F-transform
Differential equation
Boundary value problem
Second order differential equation
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
15
40
10.22111/ijfs.2017.3496
3496
مقاله پژوهشی
DIAGNOSIS OF BREAST LESIONS USING THE LOCAL CHAN-VESE MODEL, HIERARCHICAL FUZZY PARTITIONING AND FUZZY DECISION TREE INDUCTION
Fouzia Boutaouche
boutaouche-f@netcourrier.com
1
Nacéra Benamrane
2
laboraoire SIMPA, Departement d'informatique, Faculte des mathematiques et d'informatique, Universite des sciences et de la technologie d'Oran "Mohamed BOUDIAF", USTO-MB; BP 1505 El M'naouer 31000, Oran, Algerie
laboratoire SIMPA, Departement d'informatique, Faculte des mathematiques et d'informatique, Universite des sciences et de la technologie d'Oran "Mohamed BOUDIAF", USTO-MB; BP 1505 El M'naouer 31000, Oran, Algerie
Breast cancer is one of the leading causes of death among women. Mammography remains today the best technology to detect breast cancer, early and efficiently, to distinguish between benign and malignant diseases. Several techniques in image processing and analysis have been developed to address this problem. In this paper, we propose a new solution to the problem of computer aided detection and interpretation for breast cancer. In the proposed approach, a Local Chan-Vese (LCV) model is used for the mass lesion segmentation step to isolate a suspected abnormality in a mammogram. In the classification step, we propose a two-step process: firstly, we use the hierarchical fuzzy partitioning (HFP) to construct fuzzy partitions from data, instead of using the only human information, available from expert knowledge, which are not sufficiently accurate and confronted to errors or inconsistencies. Secondly,fuzzy decision tree induction are proposed to extract classification knowledge from a set of feature-based examples. Fuzzy decision trees are first used to determine the class of the abnormality detected (well-defined mass, ill-defined mass, architectural distortion, or speculated masses), then, to identify the Severity of the abnormality, which can be benign or malignant. The proposed system is tested by using the images from Mammographic Image Analysis Society[MIAS] database. Experimental results show the efficiency of the proposed approach, resulting in an accuracy rate of 87, a sensitivity of 82.14%, and good specificity of 91.42
http://ijfs.usb.ac.ir/article_3496_9e3953081f1d3b480e734c66534326f0.pdf
Breast cancer
Mass segmentation
Local Chan-Vese model fuzzy decision tree
Fuzzy partitioning
Computer-aided detection
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
41
63
10.22111/ijfs.2017.3497
3497
مقاله پژوهشی
INFORMATION MEASURES BASED TOPSIS METHOD FOR MULTICRITERIA DECISION MAKING PROBLEM IN INTUITIONISTIC FUZZY ENVIRONMENT
Arunodaya Raj Mishra
1
Pratibha Rani
pratibha138@gmail.com
2
Department of Mathematics, ITM University, Gwalior- 474001, M. P., India
Department of Mathematics, Jaypee University of Engineering and Technology, Guna-473226, M. P., India
In the fuzzy set theory, information measures play a paramount role in several areas such as decision making, pattern recognition etc. In this paper, similarity measure based on cosine function and entropy measures based on logarithmic function for IFSs are proposed. Comparisons of proposed similarity and entropy measures with the existing ones are listed. Numerical results limpidly betoken the efficiency of these measures over others. An intuitionistic fuzzy weighted measures (IFWM) with TOPSIS method for multi-criteria decision making (MCDM) quandary is introduced to grade the alternatives. This approach is predicated on entropy and weighted similarity measures for IFSs. An authentic case study is discussed to rank the four organizations. To compare the different rankings, a portfolio selection problem is considered. Various portfolios have been constructed and analysed for their risk and return. It has been examined that if the portfolios are developed using the ranking obtained with proposed method, the return is increased with slight increment in risk.
http://ijfs.usb.ac.ir/article_3497_b79c7d8a35da236ddbc695172d3305b4.pdf
Fuzzy set
Intuitionistic fuzzy set
Entropy
Similarity measure
TOPSIS
MCDM
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
65
86
10.22111/ijfs.2017.3498
3498
مقاله پژوهشی
MULTIPERIOD CREDIBILITIC MEAN SEMI-ABSOLUTE DEVIATION PORTFOLIO SELECTION
Peng Zhang
zhangpeng300478@aliyun.com
1
School of Economics and Management, South China Normal University, Guangzhou 510006, P. R. China
In this paper, we discuss a multiperiod portfolio selection problem with fuzzy returns. We present a new credibilitic multiperiod mean semi- absolute deviation portfolio selection with some real factors including transaction costs, borrowing constraints, entropy constraints, threshold constraints and risk control. In the proposed model, we quantify the investment return and risk associated with the return rate on a risky asset by its credibilitic expected value and semi- absolute deviation. Since the proposed model is a nonlinear dynamic optimization problem with path dependence, we design a novel forward dynamic programming method to solve it. Finally, we provide a numerical example to demonstrate the performance of the designed algorithm and the application of the proposed model.
http://ijfs.usb.ac.ir/article_3498_174cd4e7a275172b16ebbf632749d7bd.pdf
Finance
Multiperiod portfolio selection
Mean semi-absolute deviation
Entropy constraints
The forward dynamic programming method
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
87
102
10.22111/ijfs.2017.3499
3499
مقاله پژوهشی
ON CONVERGENCE THEOREMS FOR FUZZY HENSTOCK INTEGRALS
B. M. Uzzal Afsan
1
Department of Mathematics, Sripat Singh College, Jiaganj-742123, Murshidabad, West Bengal, India
The main purpose of this paper is to establish different types of convergence theorems for fuzzy Henstock integrable functions, introduced by Wu and Gong cite{wu:hiff}. In fact, we have proved fuzzy uniform convergence theorem, convergence theorem for fuzzy uniform Henstock integrable functions and fuzzy monotone convergence theorem. Finally, a necessary and sufficient condition under which the point-wise limit of a sequence of fuzzy Henstock integrable functions is fuzzy Henstock integrable has been established.
http://ijfs.usb.ac.ir/article_3499_6f4cc2d0c57b2e8308bf4c95c9724bbb.pdf
Fuzzy number
Fuzzy number function
Fuzzy Henstock integral
Fuzzy monotone sequence
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
103
117
10.22111/ijfs.2017.3500
3500
مقاله پژوهشی
CREDIBILITY THEORY ORIENTED PREFERENCE INDEX FOR RANKING FUZZY NUMBERS
Gholamreza Hesamian
ghesamian@math.iut.ac.ir
1
Farid Bahrami
f.ahmadi@math.iut.ac.ir
2
Department of Statistics, Payame Noor University,, Tehran 19395-3697, Iran
Department of Mathematical Sciences,, Isfahan University of Technology,, Isfahan 84156-83111, Iran
This paper suggests a novel approach for ranking the most applicable fuzzy numbers, i.e. $LR$-fuzzy numbers. Applying the $alpha$-optimistic values of a fuzzy number, a preference criterion is proposed for ranking fuzzy numbers using the Credibility index. The main properties of the proposed preference criterion are also studied. Moreover, the proposed method is applied for ranking fuzzy numbers using target-rank-based methods. Some numerical examples are used to illustrate the proposed ranking procedure. The proposed preference criterion is also examined in order to compare with some common methods and the feasibility and effectiveness of the proposed ranking method is cleared via some numerical comparisons.
http://ijfs.usb.ac.ir/article_3500_c8f1b5309e61cf8692e840b8009dfcf8.pdf
Credibility index
$alpha$-optimistic values
Robustness
Reciprocity
Fuzzy target
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
119
134
10.22111/ijfs.2017.3501
3501
مقاله پژوهشی
SOME PROBABILISTIC INEQUALITIES FOR FUZZY RANDOM VARIABLES
Hamed Ahmadzade
ahmadzadeh.h.63@gmail.com
1
Mohammad Amini
mamini48@yahoo.com
2
Seyed Mahmoud Taheri
sm_taheri@yahoo.com
3
Abolghasem Bozorgnia
a.bozorgnia@khayyam.ac.ir
4
Department of Statistics, University of Sistan and Baluchestan, Zahedan, Iran
Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad 91775, Iran
Faculty of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran
Department of Statistics, Khayyam University, Mashhad, Iran
In this paper, the concepts of positive dependence and linearlypositive quadrant dependence are introduced for fuzzy random variables. Also,an inequality is obtained for partial sums of linearly positive quadrant depen-dent fuzzy random variables. Moreover, a weak law of large numbers is estab-lished for linearly positive quadrant dependent fuzzy random variables. Weextend some well known inequalities to independent fuzzy random variables.Furthermore, a weak law of large numbers for independent fuzzy random vari-ables is stated and proved.
http://ijfs.usb.ac.ir/article_3501_4354e3e5670f8d20ba3ab0bb1f95685b.pdf
Fuzzy random variable
Linearly Positive Quadrant Dependence
Independence
Law of Large Numbers
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
135
148
10.22111/ijfs.2017.3502
3502
مقاله پژوهشی
ROBUSTNESS OF THE TRIPLE IMPLICATION INFERENCE METHOD BASED ON THE WEIGHTED LOGIC METRIC
Jun Li
lijun@lut.cn
1
Chao Fu
fuchao45612@sina.com
2
School of Science, Lanzhou University of Technology, Lanzhou 730050, Gansu, China
School of Science, Lanzhou University of Technology, Lanzhou 730050, Gansu, China
This paper focuses on the robustness problem of full implication triple implication inference method for fuzzy reasoning. First of all, based on strong regular implication, the weighted logic metric for measuring distance between two fuzzy sets is proposed. Besides, under this metric, some robustness results of the triple implication method are obtained, which demonstrates that the triple implication method possesses a good behavior of robustness.
http://ijfs.usb.ac.ir/article_3502_3af181b32a04b615e978e930b50b64b4.pdf
Robustness
Triple implication method
Weighted logic metric
Weighted logic similarity degree
Fuzzy reasoning
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-30
14
6
149
164
10.22111/ijfs.2017.3503
3503
مقاله پژوهشی
ON STRATIFIED LATTICE-VALUED CONVERGENCE SPACES
Gunther Jager
g.jager@ru.ac.za, gunther.jaeger@fh-stralsund.de
1
School of Mechanical Engineering, University of Applied Sciences Stralsund, D-18435 Stralsund, Germany
In this paper we provide a common framework for different stratified $LM$-convergence spaces introduced recently. To this end, we slightly alter the definition of a stratified $LMN$-convergence tower space. We briefly discuss the categorical properties and show that the category of these spaces is a Cartesian closed and extensional topological category. We also study the relationship of our category to the categories of stratified $L$-topological spaces and of enriched $LM$-fuzzy topological spaces.
http://ijfs.usb.ac.ir/article_3503_08f77d70db13a2b7b2554e34ebcef52f.pdf
Lattice-valued convergence
$LM$-convergence space
Stratified $LMN$-convergence tower space
Stratified $LM$-filter
Stratified $L$-topological space
Enriched $LM$-fuzzy topological space
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2017-12-01
14
6
167
175
10.22111/ijfs.2017.3505
3505
Persian-translation Vol.14, No.6
http://ijfs.usb.ac.ir/article_3505_70f72100261fda6aa83bea4e659894cb.pdf