eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
0
10.22111/ijfs.2011.2870
2870
Cover vol. 8, no. 3, october 2011
http://ijfs.usb.ac.ir/article_2870_00c38aa58385d4e27951d5fc93c237ec.pdf
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-17
8
3
1
21
10.22111/ijfs.2011.283
283
مقاله پژوهشی
A SOLUTION TO AN ECONOMIC DISPATCH PROBLEM BY A
FUZZY ADAPTIVE GENETIC ALGORITHM
H. Nezamabadi-pour
nezam@mail.uk.ac.ir
1
S. Yazdani
sajjad.yazdani@gmail.com
2
M. M. Farsangi
mmaghfoori@mail.uk.ac.ir
3
M. Neyestani
mehdi2594@yahoo.com
4
Electrical Engineering Department, Shahid Bahonar University
of Kerman, Kerman, Iran
Electrical Engineering Department, Shahid Bahonar University of Kerman,
Kerman, Iran
Electrical Engineering Department, Shahid Bahonar University of
Kerman, Kerman, Iran
Electrical Engineering Department, Shahid Bahonar University of
Kerman, Kerman, Iran
In practice, obtaining the global optimum for the economic dispatch {bf (ED)}problem with ramp rate limits and prohibited operating zones is presents difficulties. This paper presents a new andefficient method for solving the economic dispatch problem with non-smooth cost functions using aFuzzy Adaptive Genetic Algorithm (FAGA). The proposed algorithm deals with the issue ofcontrolling the exploration and exploitation capabilities of a heuristic search algorithm in whichthe real version of Genetic Algorithm (RGA) is equipped with a Fuzzy Logic Controller (FLC)which can efficiently explore and exploit optimum solutions. To validate the results obtainedby the proposed FAGA, it is compared with a Real Genetic Algorithm (RGA). Moreover, the resultsobtained by FAGA and RGA are also compared with those obtained by other approaches reported in the literature.It was observed that the FAGA outperforms the other methods in solving the power system economicload dispatch problem in terms of quality, as well as convergence and success rates.
http://ijfs.usb.ac.ir/article_283_e8f1a7a622ced9b8eb173f4167349fec.pdf
Economic dispatch
Genetic algorithm
%Fuzzy adaptive genetic algorithm
Non-smooth cost functions
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-17
8
3
23
33
10.22111/ijfs.2011.284
284
مقاله پژوهشی
Fuzzy relations, Possibility theory, Measures of uncertainty, Mathematical modeling.
Michael Gr. Voskoglou
voskoglou@teipat.gr
1
Graduate Technological Educational Institute (T.E.I.),
School of Technological Applications, 263 34 Patras, Greece
A central aim of educational research in the area of mathematical modeling and applications is to recognize the attainment level of students at defined states of the modeling process. In this paper, we introduce principles of fuzzy sets theory and possibility theory to describe the process of mathematical modeling in the classroom. The main stages of the modeling process are represented as fuzzy sets in a set of linguistic labels indicating the degree of a student's success in each of these stages. We use the total possibilistic uncertainty on the ordered possibility distribution of all student profiles as a measure of the students' modeling capacities and illustrate our results by application to a classroom experiment.
http://ijfs.usb.ac.ir/article_284_9bab58dbf42b5b3133cbad5825aa1e52.pdf
Fuzzy relations
Possibility theory
Measures of uncertainty
Mathematical modeling
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-17
8
3
35
43
10.22111/ijfs.2011.285
285
مقاله پژوهشی
Optimal Control with Fuzzy Chance Constraints
Saeed Ramezanzadeh
ramezanzadeh@phd.pnu.ac.ir
1
Aghileh Heydari
a_heidari@pnu.ac.ir
2
Department of Mathematics, Payame Noor University, Tehran,
Iran and Department of Mathematics, Faculty of Technology, Olum Entezami University,
Tehran, Iran
Department of Mathematics, Payame Noor University, Mashhad,
Iran
In this paper, a model of an optimal control problem with chance constraints is introduced. The parametersof the constraints are fuzzy, random or fuzzy random variables. Todefuzzify the constraints, we consider possibility levels. Bychance-constrained programming the chance constraints are converted to crisp constraints which are neither fuzzy nor stochastic and then the resulting classical optimalcontrol problem with crisp constraints is solved by thePontryagin Minimum Principle and Kuhn-Tucker conditions. The modelis illustrated by two numerical examples.
http://ijfs.usb.ac.ir/article_285_4e09bdb20249d87c4d326aba52f5de42.pdf
Fuzzy random
variable
Chance-constrained programming
Possibility
level
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-17
8
3
45
66
10.22111/ijfs.2011.286
286
مقاله پژوهشی
AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS
MODEL FOR TIME SERIES FORECASTING
Mehdi Khashe
khashei@in.iut.ac.ir
1
Mehdi Bijari
bijari@cc.iut.ac.ir
2
Seyed Reza Hejazi
rehejazi@cc.iut.ac.ir
3
Industrial Engineering Department, Isfahan University of Technol-
ogy, Isfahan, Iran
Industrial Engineering Department, Isfahan University of Technology,
Isfahan, Iran
Industrial Engineering Department, Isfahan University of Tech-
nology, Isfahan, Iran
Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series forecasting, usingautoregressive integrated moving average models. In the proposedmodel, by first modeling the linear components, autoregressive integrated moving average models arecombined with the these hybrid models to yield amore general and accurate forecasting model than thetraditional hybrid artificial neural networks and fuzzy models. Empirical results for financialtime series forecasting indicate that the proposed model exhibitseffectively improved forecasting accuracy and hence is an appropriate forecasting tool for financial timeseries forecasting.
http://ijfs.usb.ac.ir/article_286_8f60e4aa7f4205bae77bc7d15817e122.pdf
Auto-regressive integrated moving average (ARIMA)
Artificial neural networks (ANNs)
Fuzzy regression
fuzzy logic
Time series forecasting
Financial markets
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
67
79
10.22111/ijfs.2011.287
287
مقاله پژوهشی
T-S FUZZY MODEL-BASED MEMORY CONTROL FOR
DISCRETE-TIME SYSTEM WITH RANDOM INPUT DELAY
Jinliang Liu
liujinliang@vip.163.com
1
Zhou Gu
guzhouok@yahoo.com.cn
2
Hua Han
2070967@mail.dhu.edu.cn
3
Songlin Hu
songlin621@126.com
4
Department of Applied Mathematics, Nanjing University of Finance
and Economics, Nanjing, 210046, P. R. China and the College of Information Sciences,
Donghua University, Shanghai, 201620, P. R. China
Power Engineering, Nanjing Normal University, Nanjing, Jiangsu, 210042,
P. R. China
College of Information Science and Technology, Donghua University,
Shanghai, 201620, P. R.China
Department of Control Science and Engineering, Huazhong University
of Science and Technology, Wuhan, Hubei, 430074, P. R. China
A memory control for T-S fuzzy discrete-time systems with sto- chastic input delay is proposed in this paper. Dierent from the common assumptions on the time delay in the existing literatures, it is assumed in this paper that the delays vary randomly and satisfy some probabilistic dis- tribution. A new state space model of the discrete-time T-S fuzzy system is derived by introducing some stochastic variables satisfying Bernoulli random binary distribution and using state augmentation method, some criterion for the stochastic stability analysis and stabilization controller design are derived for T-S fuzzy systems with stochastic time-varying input delay. Finally, a nu- merical example is given to demonstrate the eectiveness and the merit of the proposed method.
http://ijfs.usb.ac.ir/article_287_efae2eb122d0757d907537e26d6bc7e6.pdf
Memory control
Fuzzy system
Random input delay
Discrete-time
system
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
81
94
10.22111/ijfs.2011.288
288
گزارش تحقیقی
EXPECTED PAYOFF OF TRADING STRATEGIES INVOLVING
EUROPEAN OPTIONS FOR FUZZY FINANCIAL MARKET
Zhongfeng Qin
qin@buaa.edu.cn, qzf05@mails.tsinghua.edu.cn
1
Xiang Li
xiang-li04@mail.tsinghua.edu.cn
2
School of Economics and Management, Beihang University, Beijing
100191, China
The State Key Laboratory of Rail Traffic Control and Safety, Beijing
Jiaotong University, Beijing 100044, China
Uncertainty inherent in the financial market was usually consid- ered to be random. However, randomness is only one special type of uncer- tainty and appropriate when describing objective information. For describing subjective information it is preferred to assume that uncertainty is fuzzy. This paper defines the expected payoof trading strategies in a fuzzy financial market within the framework of credibility theory. In addition, a computable integral form is obtained for expected payoof each strategy.
http://ijfs.usb.ac.ir/article_288_bb59ddc4aacf0649fad5e0dd252ffed3.pdf
Credibility measure
Liu process
Expected value
Fuzzy process
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
95
111
10.22111/ijfs.2011.289
289
مقاله پژوهشی
AGILITY EVALUATION IN PUBLIC SECTOR USING FUZZY
LOGIC
Nazar Dahmardeh
nazar@hamoon.usb.ac.ir
1
vahid Pourshahabi
pourshahabi.vahid@gmail.com
2
Department of Economics, University of Sistan and Baluchestan,
Zahedan, Iran
Member of Young Researchers Club, Islamic Azad University,
Zahedan, Iran
Agility metrics are difficult to define in general, mainly due to the multidimensionality and vagueness of the concept of agility itself. In this paper, a knowledge-based framework is proposed for the measurement and assessment of public sector agility using the A.T.Kearney model. Fuzzy logic provides a useful tool for dealing with decisions in which the phenomena are imprecise and vague. In the paper, we use the absolute agility index together with fuzzy logic to address the ambiguity in agility evaluation in public sector in a case study.
http://ijfs.usb.ac.ir/article_289_827b59516d05499a98dc48a20937df47.pdf
Agility index
Agility measuring
fuzzy logic
Agile government
Public
sector
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
113
124
10.22111/ijfs.2011.290
290
مقاله پژوهشی
FUZZY GOULD INTEGRABILITY ON ATOMS
Alina Cristiana Gavrilut
gavrilut@uaic.ro
1
Faculty of Mathematics, Al. I. Cuza University, Iasi,
Romania
In this paper we study the relationships existing between total measurability in variation and Gould type fuzzy integrability (introduced and studied in [21]), giving a special interest on their behaviour on atoms and on finite unions of disjoint atoms. We also establish that any continuous real valued function defined on a compact metric space is totally measurable in the variation of a regular finitely purely atomic multisubmeasure and it is also Gould integrable with respect to regular finitely purely atomic multisubmeasures.
http://ijfs.usb.ac.ir/article_290_b34c259b2551ddd12d42404e31bf5bb9.pdf
Fuzzy Gould integral
Totally measurability (in variation)
(Multi)
(sub) measure
Atom
Finitely purely atomic
regularity
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
125
135
10.22111/ijfs.2011.291
291
مقاله پژوهشی
ON GENERAL FUZZY RECOGNIZERS
M. Horry
mohhorry@chamran-edu.ir
1
M. M. Zahedi
zahedi mm@mail.uk.ac.ir
2
Shahid Chamran University of Kerman, Kerman, Iran
Department of Mathematics, Shahid Bahonar University of Kerman,
Kerman, Iran
In this paper, we de ne the concepts of general fuzzy recognizer, language recognized by a general fuzzy recognizer, the accessible and the coac- cessible parts of a general fuzzy recognizer and the reversal of a general fuzzy recognizer. Then we obtain the relationships between them and construct a topology and some hypergroups on a general fuzzy recognizer.
http://ijfs.usb.ac.ir/article_291_7143a73b4b2bcbd29a9bb6ed63d06f47.pdf
(General) Fuzzy automata
General fuzzy recognizer
Accessibility
Coaccessibility
Topology
Hypergroup
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
137
147
10.22111/ijfs.2011.292
292
مقاله پژوهشی
FUZZY SOFT SET THEORY AND ITS APPLICATIONS
Naim Cagman
naim.cagman@gop.edu.tr
1
Serdar Enginoglu
serdar.enginoglu@gop.edu.tr
2
Filiz Citak
filiz.citak@gop.edu.tr
3
Department of Mathematics, Faculty of Arts and Sciences, Gazios-
manpasa University, 60150 Tokat, Turkey
Department of Mathematics, Faculty of Arts and Sciences, Gazios-
manpasa University, 60150 Tokat, Turkey
Department of Mathematics, Faculty of Arts and Sciences, Gaziosman-
pasa University, 60150 Tokat, Turkey
In this work, we define a fuzzy soft set theory and its related properties. We then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. Finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.
http://ijfs.usb.ac.ir/article_292_22928400ec0d727700fd251a4f63fa07.pdf
Fuzzy sets
Soft sets
Fuzzy soft sets
Soft aggregation
Fuzzy soft
aggregation
Aggregate fuzzy set
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-18
8
3
149
158
10.22111/ijfs.2011.293
293
مقاله پژوهشی
ON FUZZY UPPER AND LOWER CONTRA-CONTINUOUS
MULTIFUNCTIONS
mohsen Alimohammady
amohsen@umz.ac.ir
1
E. Ekici
eekici@comu.edu.tr
2
S. Jafari
jafari@stofanet.dk
3
M. Roohi
mehdi.roohi@gmail.com
4
Department of Mathematics, University of Mazandaran, Babolsar,
Iran
Department of Mathematics, Canakkale Onsekiz Mart University, Terzioglu
Campus, 17020 Canakkale, Turkey
College of Vestsjaelland South, Herrestraede 11, 4200 Slagelse, Denmark
Ghaemshahr branch Islamic Azad University, Ghaemshahr, Iran
This paper is devoted to the concepts of fuzzy upper and fuzzy lower contra-continuous multifunctions and also some characterizations of them are considered.
http://ijfs.usb.ac.ir/article_293_e763f5996120648619462d585714b4b9.pdf
Fuzzy topological space
Fuzzy multifunctions
Fuzzy lower contracontinuous
multifunction
Fuzzy upper contra-continuous multifunction
eng
University of Sistan and Baluchestan
Iranian Journal of Fuzzy Systems
1735-0654
1735-0654
2011-10-19
8
3
161
171
10.22111/ijfs.2011.2871
2871
Persian-translation vol. 8, no. 3, october 2011
http://ijfs.usb.ac.ir/article_2871_59c5f318f5712ee069575b099e9c9c90.pdf