IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.2702 unavailable Cover vol. 10, no. 4, August 2013 29 08 2013 10 4 0 0 18 10 2016 18 10 2016 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_2702.html

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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1044 Research Paper FUZZY EQUATIONAL CLASSES ARE FUZZY VARIETIES Budimirovic Branka College for professional studies for teachers, Sabac, Serbia Budimirovic Vjekoslav College for professional studies for teachers,Sabac, Mega- trend University, Beograd, Serbia Seselja Branimir  Department of Mathematics and Informatics, University of Novi Sad, Novi Sad, Serbia Tepavcevic Andreja Department of Mathematics and Informatics, University of Novi Sad, Novi Sad, Serbia 30 08 2013 10 4 1 18 07 03 2012 07 11 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1044.html

In the framework of fuzzy algebras with fuzzy equalities and acomplete lattice as a structure of membership values, we investigate fuzzyequational classes. They consist of special fuzzy algebras ful lling the samefuzzy identities, de ned with respect to fuzzy equalities. We introduce basicnotions and the corresponding operators of universal algebra: construction offuzzy subalgebras, homomorphisms and direct products. We prove that everyfuzzy equational class is closed under these three operators, which means thatsuch a class is a fuzzy variety.

fuzzy algebra Fuzzy identity Fuzzy equality Fuzzy homomorphism Fuzzy direct product Fuzzy equational class Fuzzy variety
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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1045 Research Paper A NEW ANALYTICAL METHOD FOR SOLVING FUZZY DIFFERENTIAL EQUATIONS Lata Sneh School of Mathematics and Computer Applications, Thapar University, Patiala, 147004, India Kumar Amit School of Mathematics and Computer Applications, Thapar Univer- sity, Patiala, 147004, India 30 08 2013 10 4 19 39 07 10 2011 07 09 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1045.html

In the literature, several numerical methods are proposed for solvingnth-order fuzzy linear diff erential equations. However, till now there areonly two analytical methods for the same. In this paper, the fuzzy Kolmogorov'sdi fferential equations, obtained with the help of fuzzy Markov modelof piston manufacturing system, are solved by one of these analytical methodsand illustrated that the obtained solution does not represent a fuzzy number.To resolve the drawback of existing method, a new analytical method is proposedfor solving nth-order fuzzy linear di fferential equations. Furthermore,the advantage of proposed method over existing method is also discussed.

Fuzzy di fferential equations Fuzzy Kolmogorov's diff erential equations LR flat fuzzy number JMD LR flat fuzzy number Fuzzy reliability Fuzzy Markov model Piston manufacturing system
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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1046 Research Paper A QUADRATIC MARGIN-BASED MODEL FOR WEIGHTING FUZZY CLASSIFICATION RULES INSPIRED BY SUPPORT VECTOR MACHINES Taheri Mohammad Department of Computer Science & Engineering & IT, Shiraz University, Shiraz, Fars, Iran Azad Hamid Department of Electrical Engineering, Science & Research Branch, Islamic Azad University, Marvdasht, Fars, Iran Ziarati Koorush Department of Computer Science & Engineering & IT, Shiraz Uni- versity, Shiraz, Fars, Iran Sanaye Reza Department of Computer Science & Engineering & IT, Shiraz Univer- sity, Shiraz, Fars, Iran 30 08 2013 10 4 41 55 07 04 2012 07 11 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1046.html

Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only  considers both accuracy and generalization criteria in a single objective function, but also is independent of any order in presenting data patterns or fuzzy rules. It has a global optimum solution and needs only one regularization parameter C to be adjusted. In addition, a rule reduction method is proposed to eliminating low weighted rules and having a compact rule-base. This method is compared with some greedy, reinforcement and local search rule weighting methods on 13 standard datasets. The experimental results show that, the proposed method significantly outperforms the other ones especially from the viewpoint of generalization.

Classification algorithms Fuzzy systems Margin maximization Rule weighting Support vector machines
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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1047 Research Paper A FUZZY VERSION OF HAHN-BANACH EXTENSION THEOREM Zedam Lemnaouar Department of Mathematics, Faculty of Mathematics and Infor- matics, M'sila University, P.O.Box 166 Ichbilia, M'sila 28105, Algeria 30 08 2013 10 4 57 66 07 12 2010 07 09 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1047.html

In this paper, a fuzzy version of the analytic form of Hahn-Banachextension theorem is given. As application, the Hahn-Banach theorem for$r$-fuzzy bounded linear functionals on $r$-fuzzy normedlinear spaces is obtained.

Fuzzy order $r$-fuzzy bounded linear functional $r$-fuzzy norm $r$-fuzzy Hahn-Banach theorem
bibitem{Amrdav11} A. Amroune and B. Davvaz, {it Fuzzy ordered sets and duallity for finite fuzzy distributive lattices}, Iranian Journal of Fuzzy Systems, {bf 8}textbf{(5)} (2011), 1--12. bibitem{BaSa05} T. Bag and S. K. Samanta, {it Fuzzy bounded linear operators}, Fuzzy Sets and Systems, textbf{151} (2005), 513--547. bibitem{Beg04} I. Beg, {it Some applications of fuzzy ordered relations}, CUBO, textbf{6(1)} (2004), 103--114. bibitem{Ber95} B. M. Bernadette, {it La logique floue et ses applications}, Addison-Wesley, Paris, 1995. bibitem{Bil92} A. Billot, {it Economic theory of fuzzy equilibria}, Lecture Notes in Economics and Mathematical systems-373, Springer-Verlag, Berlin, 1992. bibitem{BS04} P. Binimol and A. S. Kuriakose, {it Fuzzy Hahn-Banach Theorem-a new approch I}, J. Fuzzy Math., textbf{12(1)} (2004), 127-1363. bibitem{BS05} P. Binimol and A. S. Kuriakose, {it Fuzzy Hahn-Banach Theorem-a new approch II}, J. Fuzzy Math., textbf{13(1)} (2005), 25-33. bibitem{Bod07} U. Bodenhofer , B. De Baets and F. Janos , {it A compendium of fuzzy weak orders: representations and constructions}, Fuzzy Sets and Systems, textbf{158} (2007), 811-829. bibitem{ItCho98} M. Itoh and M. Cho, {it Fuzzy bounded operators}, Fuzzy Sets and Systems, textbf{93} (1998), 353-362. bibitem{Kundu00} S. Kundu, {it Similarity relations, fuzzy linear orders and fuzzy partial orders}, Fuzzy Sets and Systems, textbf{109} (2000), 419-428. bibitem{Liyen95} H. X. Li and V. C. Yen, {it Fuzzy sets and fuzzy decision-making}, CRC Press. Inc., London, 1995. bibitem{NVT07} A. Narayanan, S. Vijayabalajt and N. Thillaigovindan, {it Intuitionistic fuzzy bounded linear operators}, Iranian Journal of Fuzzy Systems, {bf 4}textbf{(1)} (2007), 89--101. bibitem{Ovch91} S. V. Ovchinnikov, {it Similarity relations, fuzzy partitions, and fuzzy ordering}, Fuzzy Sets and Systems, textbf{40} (1991), 107-126. bibitem{Ovch2000} S. V. Ovchinnikov, {it An introduction to fuzzy relations}, In D. Dubois, H. Prade, Fundamentals of Fuzzy Sets, The Handbooks of fuzzy sets, Kluwer Academic Publisher, Boston, {bf7} (2000), 233-259. bibitem{Ram99} T. V. Ramakrishnan, {it A fuzzy extension of Hahn-Banach Theorem}, J. Fuzzy Math., textbf{7(3)} (1999), 620-630. bibitem{RH99} G. S. Rhie and I. A. Hwang, {it On the fuzzy Hahn-Banach theorem-an analytic form}, Fuzzy Sets and Systems, textbf{108} (1999), 117-121. bibitem{StZed} A. Stouti and L. Zedam, {it On $alpha$-fuzzy orders}, J. Fuzzy Math., textbf{18(1)} (2010), 171-192. bibitem{Ven92} P. Venugopalan, {it Fuzzy ordered sets}, Fuzzy Sets and Systems, textbf{46} (1992), 221-226. bibitem{Xiao02}  J. Z. Xiao, {it Hahn-Banach theorem for fuzzy normed spaces}, J. Baoji College Arts Sci.Nat. Sci., textbf{22(1)} (2002), 11-14. bibitem{Zadeh65} L. A. Zadeh, {it Fuzzy sets}, Information and Control, textbf{8} (1965), 338-353. bibitem{Zadeh71} L. A. Zadeh, {it Similarity relations and fuzzy orderings}, Information Sciences, textbf{3} (1971), 177-200. bibitem{Zim91} H. J. Zimmermann, {it Fuzzy set theory and its applications}, Kluwer Academic Publisher, Dordrecht, 1991.
IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1048 Research Paper APPLICATION OF PREFERENCE RANKING ORGANIZATION METHOD FOR ENRICHMENT EVALUATION METHOD IN ENERGY PLANNING - REGIONAL LEVEL Khatami Firouzabadi Ali Allameh Tabatabai University Business School (ATUBS), Tehran, Iran Ghazimatin Elham Allameh Tabatabai University Business School (ATUBS), Tehran, Iran 30 08 2013 10 4 67 81 07 11 2011 07 12 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1048.html

Nowadays energy is one of the most essential needs of human being and it can be considered as the basic prerequisite of social and economic development.  Hence, many of the correlations and legislations of a country are affected by it. Since Iran has huge source of gas and oil, it has turned to a fossil fuel oriented county. But as oil and gas sources are non-renewable ones and cannot be replaced, it is essential for every country to focus on Renewable Energy Sources (RES). So today is the time of studying and investing on RES to be able to exploit them in the time of oil and gas crisis. In the past, the choice among alternative sources was based on the cost minimization, but ranking the RES optionsâ€™ is a complex task. The objective of this paper is determining the best renewable energy alternative for Sistan & Baluchestan province of Iran by using interval Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method. In the application of the proposed methodology the most appropriate renewable energy alternative is determined fuel cell and biomass for the mentioned province.

renewable energy Criteria Alternative Interval PROMETHEE
IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1049 Research Paper BILEVEL LINEAR PROGRAMMING WITH FUZZY PARAMETERS Hamidi Farhad Faculty of Mathematics, University of Sistan and Baluchestan, Za- hedan, Iran Mishmast Nehi Hassan Faculty of Mathematics, University of Sistan and Baluches- tan, Zahedan, Iran 30 08 2013 10 4 83 99 07 07 2011 07 09 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1049.html

Bilevel linear programming  is a decision making problem with a two-level decentralized organization. The textquotedblleft leadertextquotedblright~ is in the upper level and the textquotedblleft followertextquotedblright, in the lower. Making a decision at one level affects that at the other one. In this paper, bilevel linear programming  with inexact parameters has been studied and a method is proposed to solve a fuzzy bilevel linear programming  using  interval bilevel linear programming.

Fuzzy numbers Interval numbers Bilevel programming Hierarchical optimization
IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1050 Research Paper REVISION OF SIGN DISTANCE METHOD FOR RANKING OF FUZZY NUMBERS Abbasbandy Saeid Department of Mathematics, Science and Research Branch, Is- lamic Azad University, Tehran, Iran Nuraei Rahele Department of Mathematics, South Tehran Branch, Islamic Azad University, Tehran, Iran Ghanbari Mojtaba Department of Mathematics, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran 30 08 2013 10 4 101 117 07 04 2011 07 11 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1050.html

Recently, Abbasbandy and Asady have been proposed a modificationof the distance based approach, namely sign distance method''.However, in this paper, it is shown that this method has some drawbacks, i.e.,the result is not consistent with human intuition for specialcases and this method cannot always logically infer rankingorder of the images of the fuzzy numbers. In this paper, wepresent a revised method which can avoid these problems forranking fuzzy numbers. Also, we present several propertiesfor revised sign distance method while the original method does not have some ofthem.

Fuzzy number Ranking of fuzzy numbers Sign distance method Revised sign distance method
IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1051 Research Paper A NOTE ON THE RELATIONSHIP BETWEEN HUTTON'S QUASI-UNIFORMITIES AND SHI'S QUASI-UNIFORMITIES Yue Yueli Department of Mathematics, Ocean University of China, 238 Songling Road, 266100, Qingdao, P.R.China 29 08 2013 10 4 119 124 07 10 2011 07 10 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1051.html

This note studies the relationship between Hutton's quasi-uniformities and Shi's quasi-uniformities. It is shown that when $L$ satisfiesmultiple choice principle" for co-prime elements, the category of Hutton's quasi-uniform spaces is a bireflective full subcategory of the category of Shi's quasi-uniform spaces. Especially, if the remote-neighborhood mapping defined by Shi preserves arbitrary joins, then the two categories are isomorphic to each other.

Hutton's quasi-uniformity Shi's quasi-uniformity Reflective category
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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1052 Research Paper Fixed point theory for cyclic $varphi$-contractions in fuzzy metric spaces Shen Yong-hong School of Mathematics and Statistics, Tianshui Normal Univer- sity, Tianshui 741001, People's Republic of China Qiu Dong College of Mathematics and Physics, Chongqing University of Posts and Telecommunications, Chongqing 400065, People's Republic of China Chen Wei School of Information, Capital University of Economics and Business, Beijing, 100070, People's Republic of China 30 08 2013 10 4 125 133 07 12 2011 07 10 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1052.html

In this paper, the notion of cyclic $varphi$-contraction in fuzzymetric spaces is introduced and a fixed point theorem for this typeof mapping is established. Meantime, an example is provided toillustrate this theorem. The main result shows that a self-mappingon a G-complete fuzzy metric space has a unique fixed point if itsatisfies the cyclic $varphi$-contraction. Afterwards, some results inconnection with the fixed point are given.

Cyclic representation Cyclic $\varphi$-contraction Fixed point G-Cauchy sequence G-complete fuzzy metric space
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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.1053 Research Paper A NOTE ON STRATIFIED LM-FILTERS Jager Gunther Department of Statistics, Rhodes University, 6140 Grahamstown, South Africa 30 08 2013 10 4 135 142 07 02 2012 07 12 2012 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_1053.html

We develop a theory of stratified $LM$-filters which generalizes the theory of stratified $L$-filters. Our stratification condition explicitly depends on a suitable mapping between the lattices $L$ and $M$. If $L$ and $M$ are identical and the mapping is the identity mapping, then we obtain the theory of stratified $L$-filters. Based on the stratified $LM$-filters, a general theory of lattice-valued convergence spaces can be developed.

$LM$-filter Stratification Stratified $LMN$-convergence space
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IJFS University of Sistan and Baluchestan Iranian Journal of Fuzzy Systems 1735-0654 University of Sistan and Baluchestan 21 10.22111/ijfs.2013.2703 unavailable Persian-translation vol. 10, no. 4, August 2013 29 08 2013 10 4 145 154 18 10 2016 18 10 2016 Copyright © 2013, University of Sistan and Baluchestan. 2013 http://ijfs.usb.ac.ir/article_2703.html

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