Cover vol. 12, no.5, October 2015
text
article
2015
eng
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
0
http://ijfs.usb.ac.ir/article_2642_e38b90e7cce4505fe17c4f2f1a961d07.pdf
dx.doi.org/10.22111/ijfs.2015.2642
Functorial semantics of topological theories
Sergey A.
Solovyov
Institute of Mathematics, Faculty of Mechanical Engineering,
Brno University of Technology, Technicka 2896/2, 616 69 Brno, Czech Republic
author
text
article
2015
eng
Following the categorical approach to universal algebra through algebraic theories, proposed by F.~W.~Lawvere in his PhD thesis, this paper aims at introducing a similar setting for general topology. The cornerstone of the new framework is the notion of emph{categorically-algebraic} (emph{catalg}) emph{topological theory}, whose models induce a category of topological structures. We introduce the quasicategory of catalg topological theories and consider its functorial relationships with the quasicategory of the categories of models, in order to provide convenient means for studying topological structures via the properties of their corresponding theories.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
1
43
http://ijfs.usb.ac.ir/article_2110_e9eb0f65766fb9dfb4d98bd6fea53fbc.pdf
dx.doi.org/10.22111/ijfs.2015.2110
CVaR Reduced Fuzzy Variables and Their Second Order Moments
Xue-Jie
Bai
College of Management, Hebei University, Baoding 071002, Hebei, China and College of Science, Agricultural University of Hebei, Baoding 071001, Hebei, China
author
Yan-Kui
Liu
College of Management, Hebei University, Baoding 071002, Hebei,
China
author
text
article
2015
eng
Based on credibilistic value-at-risk (CVaR) of regularfuzzy variable, we introduce a new CVaR reduction method fortype-2 fuzzy variables. The reduced fuzzy variables arecharacterized by parametric possibility distributions. We establishsome useful analytical expressions for mean values and secondorder moments of common reduced fuzzy variables. The convex properties of second order moments with respect to parameters are also discussed. Finally, we take second order moment as a new risk measure, and develop a mean-moment model to optimize fuzzy portfolio selection problems. According to the analytical formulas of second order moments, the mean-moment optimization model is equivalent to parametricquadratic convex programming problems, which can be solved by general-purpose optimization software. The solution results reported in the numerical experiments demonstrate the credibility of the proposed optimization method.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
45
75
http://ijfs.usb.ac.ir/article_2111_ae9c29c1bd509c95fc8928b9778558da.pdf
dx.doi.org/10.22111/ijfs.2015.2111
Linear matrix inequality approach for synchronization of chaotic fuzzy cellular neural networks with discrete and unbounded distributed delays based on\ sampled-data control
P.
Balasubramaniam-pour
Department of Mathematics, Gandhigram Rural Institute - Deemed University, Gandhigram - 624 302, Tamilnadu, India
author
K.
Ratnavelu
Institute of Mathematical Sciences, Faculty of Science, University
of Malaya - 50603, Kuala Lumpur, Malaysia
author
M.
Kalpana
Institute of Mathematical Sciences, Faculty of Science, University of
Malaya - 50603, Kuala Lumpur, Malaysia
author
text
article
2015
eng
In this paper, linear matrix inequality (LMI) approach for synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete and unbounded distributed delays based on sampled-data controlis investigated. Lyapunov-Krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of LMIs ensuring the delayed FCNNs to be asymptotically synchronous. The restriction such as the time-varying delay required to be differentiable or even its time-derivative assumed to be smaller than one, are removed. Instead, the time-varying delay is only assumed to be bounded. Finally, numerical examples and its simulations are provided to demonstrate the effectiveness of the derived results.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
77
98
http://ijfs.usb.ac.ir/article_2112_42c61297c52cf75dfbd00eb52c889040.pdf
dx.doi.org/10.22111/ijfs.2015.2112
Hierarchical Functional Concepts for Knowledge Transfer among Reinforcement Learning Agents
A.
Mousavi
Control and Intelligent Processing Center of Excellence, School of
Electrical and Computer Engineering, University of Tehran, Tehran, Iran
author
M.
Nili Ahmadabadi
Control and Intelligent Processing Center of Excellence,
School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
and School of Cognitive Science, Institute for Research in Fundamental Sciences
(IPM), Tehran, Iran
author
H.
Vosoughpour
Control and Intelligent Processing Center of Excellence, School
of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
author
B. N.
Araabi
Control and Intelligent Processing Center of Excellence, School of
Electrical and Computer Engineering, University of Tehran, Tehran, Iran and School
of Cognitive Science, Institute for Research in Fundamental Sciences (IPM), Tehran,
Iran
author
N.
Zaare
Control and Intelligent Processing Center of Excellence, School of
Electrical and Computer Engineering, University of Tehran, Tehran, Iran
author
text
article
2015
eng
This article introduces the notions of functional space and concept as a way of knowledge representation and abstraction for Reinforcement Learning agents. These definitions are used as a tool of knowledge transfer among agents. The agents are assumed to be heterogeneous; they have different state spaces but share a same dynamic, reward and action space. In other words, the agents are assumed to have different representations of an environment while having similar actions. The learning framework is $Q$-learning. Each dimension of the functional space is the normalized expected value of an action. An unsupervisedclustering approach is used to form the functional concepts as some fuzzy areas in the functional space. The functional concepts are abstracted further in a hierarchy using the clustering approach. The hierarchical concepts are employed for knowledge transfer among agents. Properties of the proposed approach are tested in a set of case studies. The results show that the approach is very effective in transfer learning among heterogeneous agents especially in the beginning episodes of the learning.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
99
116
http://ijfs.usb.ac.ir/article_2113_282ba69af4a0a581fecc56675062be1d.pdf
dx.doi.org/10.22111/ijfs.2015.2113
Non-Newtonian Fuzzy numbers and \related applications
Ugur
Kadak
Department of Mathematics, Bozok University, Yozgat, Turkey
author
text
article
2015
eng
Although there are many excellent ways presenting the principle of the classical calculus, the novel presentations probably leads most naturally to the development of the non-Newtonian calculus. The important point to note is that the non-Newtonian calculus is a self-contained system independent of any other system of calculus. Since this self-contained work is intended for a wide audience, including engineers, scientists and mathematicians. The main purpose of the present paper is to construct of fuzzy numbers with respect to the non-Newtonian calculus and is to give the necessary and sufficient conditions according to the generalization of the notion of fuzzy numbers by using the generating functions. Also we introduce the concept of non-Newtonian fuzzy distance and give some properties regarding convergence of sequences and series of fuzzy numbers with some illustrative examples.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
117
137
http://ijfs.usb.ac.ir/article_2114_aafefe9d564507d2db1e4749261bbf48.pdf
dx.doi.org/10.22111/ijfs.2015.2114
Order intervals in the metric space\ of fuzzy numbers
S.
Aytar
Faculty of Arts and Sciences, Department of Mathematics, Suleyman
Demirel University, Isparta, Turkey
author
text
article
2015
eng
In this paper, we introduce a function in order to measure the distancebetween two order intervals of fuzzy numbers, and show that this function isa metric. We investigate some properties of this metric, and finally presentan application. We think that this study could provide a more generalframework for researchers studying on interval analysis, fuzzy analysis andfuzzy decision making.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
139
147
http://ijfs.usb.ac.ir/article_2115_28bfba3b526dd2943ba3639b4db69957.pdf
dx.doi.org/10.22111/ijfs.2015.2115
A note on soft topological spaces
Fu-Gui
Shi
School of Mathematics and Statistics, Beijing Institute of Technology,
5 South Zhongguancun Street, Haidian District, 100081 Beijing, P.R. China
author
Bin
Pang
School of Mathematics and Statistics, Beijing Institute of Technology, 5
South Zhongguancun Street, Haidian District, 100081 Beijing, P. R. China
author
text
article
2015
eng
This paper demonstrates the redundancies concerning the increasing popular ``soft set" approaches to general topologies. It is shown that there is a complement preserving isomorphism (preserving arbitrary $widetilde{bigcup}$ and arbitrary $widetilde{bigcap}$) between the lattice ($mathcal{ST}_E(X,E),widetilde{subset}$) of all soft sets on $X$ with the whole parameter set $E$ as domains and the powerset lattice ($mathcal{P}(Xtimes E),subseteq$) of all subsets of $Xtimes E$. It therefore follows that soft topologies are redundant and unnecessarily complicated in theoretical sense.
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
149
155
http://ijfs.usb.ac.ir/article_2116_72c56938f64cab0a8312fcbb598fa53d.pdf
dx.doi.org/10.22111/ijfs.2015.2116
Persian-translation vol. 12, no.5, October 2015
text
article
2015
eng
Iranian Journal of Fuzzy Systems
University of Sistan and Baluchestan
1735-0654
12
v.
5
no.
2015
159
165
http://ijfs.usb.ac.ir/article_2643_0921b835f0d81e0b0abec67977f149f7.pdf
dx.doi.org/10.22111/ijfs.2015.2643