International Journal of Fuzzy Systems and Advanced Applications

ISSN: 2313-0512
Volume 3, 2016

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

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Volume 3, 2016

Title of the Paper: A GIS-Supported Approach with AHP & OWA for Site Suitability Evaluation of Sustainable Rural Housings towards Ecotourism


Authors: J. S. Jeong

Pages: 54-61

Abstract: The main objective of this proposed article is to verify, evaluate and prioritize the sustainable rural housing sites for potential ecotourism under increasing pressure of recreational and tourist awareness. The research is based on the understanding of all possible aspects and implications using Geographic Information Systems (GIS) and Analytical Hierarchy Process (AHP) in a case study area, La Vera, Spain. The evaluating process for sustainable rural housings site on ecotourism is also based on Multi-Criteria Decision Analysis (MCDA). It conducted with eighteen criteria, which are involved in the computation process distinguished in four main groups: constraints, tourism resource, environmental and social-economic criteria. Those factors were selected and weighted according to a field survey of local residents and a professional expert’s discussion. Then, they evaluate the suitability of the case study area on ecotourism in order to suitably site rural buildings with the aid of Ordered Weighted Averaging (OWA) operator weighing functions together with constant value of ‘orness’ and ‘maximum entropy’. The methodology proposed herein was valuable to identify sustainable rural housings sites on ecotourism by linking the criteria deemed important with the actual resources of the case study area. The assessment results present a new empirical approach and valuable management tool for evaluating the existing infrastructure and environment and for predicting their future improvements, which can be reapplied to other destinations with similar geographical characteristics. Particularly, this method analysis proposes an approach to enhance the participatory attitudes of local residents in the sustainable assessment management.

Title of the Paper: Intelligent Control of Manipulator Robot


Authors: K. Behih, K. Benmahammed, Dj. Zehar

Pages: 47-53

Abstract: This paper contribute in elaboration of adaptive fuzzy backstepping control laws family, based on sliding mode for unknown multivariable nonlinear and perturbed systems. Thus we propose at first a control where nonlinearities will be used to construct a backstepping approach, the robustness of this later is guaranteed via sliding mode. In this combination the adaptation laws are deduced from the stability study using Lyapunov synthesis. Secondly, we use the fuzzy systems as universal approximators in order to deal with the unknown dynamic of the studied system and to approximate the switching control term of the sliding control in order to resolve the chattering problem. To illustrate the performance of this proposed algorithm an example of an unknown multivariable nonlinear system “Manipulators Robot” is given.

Title of the Paper: Using Fuzzy Knowledge Base to Evaluate Classical Potential Barrier of Reactions in Solutions of Hydrogen Atoms and Hydrocarbons


Authors: Vladimir E. Tumanov, Elena S. Amosova, Andrey I. Prokhorov

Pages: 43-46

Abstract: Chemical society watches closely the development of methods of artificial intelligence and applies them to solve their tasks. In particular it studies the use of applied methods of artificial intelligence for production of new knowledge from electronic chemical data collections. One of essential characteristics of chemical reactions is a classical potential barrier, which used when simulating the technological processes and creating the technology of new material development. However, its estimation is rather difficult task. Using of quantum chemical methods requires large enough resources and time. Our approach to the problem is to approximate the collected series of experimental data to solve it more efficiently. The purpose of this specific work is to combine using of empirical models of radical reactions of abstraction of hydrogen atoms with applied artificial intelligence methods, with fuzzy knowledge base, in order to approximate and then predict classical potential barrier of certain classes of such reactions on the basis of available empirical data. For this it was built fuzzy knowledge base on the basis of expert conclusions and Mamdani's fuzzy inference method was used. We have proposed a method that allows evaluating the value of classical potential barrier in the reaction of hydrogen atoms with hydrocarbons. It was shown, that the used method predicts the classical potential barrier of reactions in solutions of hydrogen atoms and hydrocarbons with high accuracy within a limited range of organic compounds.

Title of the Paper: Selecting the Most Appropriate Fuzzy Implication Based on Statistical Data


Authors: P. Pagouropoulos, C. D. Tzimopoulos, B. K. Papadopoulos

Pages: 32-42

Abstract: Fuzzy implications are used in inference system applications involving fuzzy control, approximate reasoning, and artificial intelligence, among others. In applications where propositional logic is employed for reasoning, fuzzy implications play a fundamental role as logical connectives. In applications where multiple fuzzy implications are to be engaged, it is necessary that the most appropriate of these implications be selected, on the grounds that it best represents the notion of induction of an application, pertaining to it. This study introduces a method for the selection of the most appropriate fuzzy implication among others under consideration. The method’s resulting most appropriate fuzzy implication is the one, whose corresponding fuzzy propositions best represent the inference making from the data of an application, regarding the expert’s opinion on the data application.

Title of the Paper: Design of a Fuzzy Supervisory Control System for a Binary Distillation Column


Authors: N. Sangster, T. Lalla, S. Mohammed

Pages: 27-31

Abstract: In a distillation column, slight changes in the flow rate of the feedstock have an effect on the operational efficiency and product quality of the column, unless some operating parameters, such as reflux rate or vapour boil up rate, are modified. Most plants have operators that monitor these variables and make the necessary adjustments to maintain the desired product quality. Most of the time then, product quality depends on the operator’s experience or his/her response time to the disturbance variable. This work looked at developing a fuzzy supervisory controller which included a feed-forward and two feedback controllers for the purpose of improving the dual product quality control of an existing pilot binary distillation column. The fuzzy system rule bases were designed using data collected from experimentation and interviews with operators. The membership functions were based on the temperature error and its rate of change. The controller actions were then simulated using the fuzzyTECH software. These outputs were compared to the experience based control values from the operators and the controllers were fine tuned to achieve a less than ten percent percentage error. Positive results were achieved as the majority of the simulated controller outputs were within 10% of the actual values.

Title of the Paper: The Notion of Duality in Fully Intuitionistic Fuzzy Linear Programming (FIFLP) Problems


Authors: Izaz Ullah Khan, Mohsin Khan

Pages: 20-26

Abstract: This study is devoted to address the notion of duality in Fully Intuitionistic Fuzzy Linear Programming Problems (FIFLP). The problem is addressed by using a revised simplex method with the Gaussian elimination process in fully intuitionistic fuzzy environment. Intuitionistic Fuzzy Trapezoidal Numbers (IFTrpN), along with the basic arithmetic techniques defined on them help in solving the (FIFLP’s). Moreover, a modified ranking function makes comparisons among intuitionistic fuzzy numbers and identifies the location of next iteration of the revised simplex method.

Title of the Paper: Linguistic Questionnaire Evaluation: an Application of the Signed Distance Defuzzification Method on Different Fuzzy Numbers. The Impact on the Skewness of the Output Distributions


Authors: Rédina Berkachy, Laurent Donzé

Pages: 12-19

Abstract: Linguistic questionnaires are one of the very challenging keys in the world of surveys, in particular considering their fuzziness and imprecision. Many approaches have been used to evaluate them. In this paper, we show the individual and global evaluations of a linguistic questionnaire using fuzzy logic, and the relation between these two evaluations. We explore, as well, the signed distance defuzzification method in the case of different types of fuzzy numbers: the triangular, trapezoidal, gaussian, bell shaped and two-sided gaussian fuzzy numbers. Furthermore, we apply this method to individual evaluations in order to highlight the skewness of the output distributions and compare it to the ones measured using other defuzzification methods. Our simulations revealed some interesting characteristics such as the skewness of distributions obtained from applying the signed distance method is constant for all the types of commonly used fuzzy numbers.

Title of the Paper: General Conditioned and Aimed Information on Fuzzy Setting


Authors: D. Vivona, M. Divari

Pages: 7-11

Abstract: In this paper our investigation on aimed information, started in 2011, will be completed on fuzzy setting. Here will be given a form of information for fuzzy sets, when it is conditioned and aimed. This information is called general,because it is defined without using probability or fuzzy measure.

Title of the Paper: Comprising Feature Selection and Classifier Methods with SMOTE for Prediction of Male Infertility


Authors: Bekir Karlık, Abdulkerim M. Yibre, Barış Koçer

Pages: 1-6

Abstract: The aim of this study is on prediction of male fertility problems by using different classifier algorithms and applying feature selection methods. Used data in this study is gathered from UCI data repository. The ratio of between normal and abnormal (alter) samples is more than 7. This indicates the dataset is originally imbalanced in order to balance the examples of the dataset SMOTE technique which is applied for a better accuracy and representative result of classifiers. Feature selection and classification methods are comprised for prediction of male fertility. In this study, MLP, Na?ve Bayes, Random Forest, KNN, and SVM classifiers were used. Comparison results show that Naive Bayes classifier has better classification accuracy as 90.65% than the others.