FCTA 2012 Abstracts

Full Papers Short Papers
Full Papers
Paper Nr: 4
Title:

Interactive Fuzzy Decision Making for Multiobjective Fuzzy Random Linear Programming Problems
Authors:

Hitoshi Yano and Masatoshi Sakawa
Abstract: In this paper, we propose an interactive fuzzy decision making method for multiobjective fuzzy random linear programming problems (MOFRLP), in which the criteria of probability maximization and fractile optimization are considered simultaneously. In the proposed method, it is assumed that the decision maker has fuzzy goals for not only objective functions of MOFRLP but also permissible probability levels in a fractile optimization model for MOFRLP, and such fuzzy goals are quantified by eliciting the corresponding membership functions. Using the fuzzy decision, such two kinds of membership functions are integrated. In the integrated membership space, the satisfactory solution is obtained from among a Pareto optimal solution set through the interaction with the decision maker.
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Paper Nr: 10
Title:

An Order Hyperresolution Calculus for Gödel Logic - General First-order Case
Authors:

Dušan Guller
Abstract: This paper addresses the deduction problem of a formula from a countable theory in the first-order G\"{o}del logic from a perspective of automated deduction. Our approach is based on the translation of a formula to an equivalent satisfiable CNF one, which contains literals of the augmented form: either a or a → b or (a→b) →b or Qx c→ a or a→Qx c where a, c are atoms different from 0 (the false), 1 (the true); b is an atom different from 1; Q ∈ {∀,∃}; x is a variable occurring in c. A CNF formula is further translated to an equivalent satisfiable finite order clausal theory, which consists of order clauses - finite sets of order literals of the form: either a ≖ b or Qx c ≖ a or a ≖ Qx c or a ≺ b or Qx c ≺ a or a ≺ Qx c where a, b, c are atoms; Q ∈ {∀,∃}; x is a variable occurring in c. ≖ and ≺ are interpreted by the equality and strict linear order on [0,1], respectively. For an input theory, the proposed translation produces a so-called semantically admissible order clausal theory. An order hyperresolution calculus, operating on semantically admissible order clausal theories, is devised. The calculus is proved to be refutation sound and complete for the countable case.
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Paper Nr: 27
Title:

Fuzzy Querying based Tool for Building Courses Evaluation Tests
Authors:

Livia Borjas, Josué Ramírez, Rosseline Rodríguez and Leonid Tineo
Abstract: In this paper, we present a tool intended for helping in exam configuration based on the reutilization of questions according to user preferences. It is a real life application of fuzzy querying that fulfils an actual need of academic personal at a high studies institution of Venezuela. This application uses the fuzzy querying language SQLf, on top of an existing relational DBMS by means a logic layer named SQLfi. Final users of our application are professors of any area without knowledge of fuzzy sets and databases. We use criteria for the test preparation that support fuzzy terms. These terms can be adjusted to user preferences. Graphic user interfaces are provided in order to perform such adjusts as well as exam configuration and any other fuzzy querying operation. We present here the Database Design, the process test construction and the management of preferences.
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Paper Nr: 28
Title:

Non-commutative Fuzzy Logic psMTL - An Alternative Proof for the Standard Completeness Theorem
Authors:

Denisa Diaconescu
Abstract: In (Jenei and Montagna, 2003) was proved that the non-commutative psMTL logic introduced in (Hájek, 2003b) is the logic of left-continuous non-commutative t-norms or, equivalently, that the logic psMTL enjoys standard completeness. In the present paper we provide an alternative proof for the standard completeness theorem for the logic psMTL and we furthermore show that this result can be obtained also for finite theories.
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Paper Nr: 31
Title:

Towards an Approach to Select Features from Low Quality Datasets
Authors:

José Manuel Cadenas, María del Carmen Garrido and Raquel Martínez
Abstract: Feature selection is an active research in machine learning. The main idea of feature selection is to choose a subset of available features, by eliminating features with little or no predictive information, and features strongly correlated. There are many approaches for feature selection, but most of them can only work with crisp data. Until our knowledge there are not many approaches which can directly work with both crisp and low quality (imprecise and uncertain) data. That is why, we propose a new method of feature selection which can handle both crisp and low quality data. The proposed approach integrates filter and wrapper methods into a sequential search procedure with improved classification accuracy of the features selected. This approach consists of steps following: (1) Scaling and discretization process of the feature set; and feature pre-selection using the discretization process (filter); (2) Ranking process of the feature pre-selection using a Fuzzy Random Forest ensemble; (3) Wrapper feature selection using a Fuzzy Decision Tree technique based on cross-validation. The efficiency and effectiveness of the approach is proved through several experiments with low quality datasets. Approach shows an excellent performance, not only classification accuracy, but also with respect to the number of features selected.
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Paper Nr: 32
Title:

Analysis of Protection of Body Slope in the Rockfill Reservoir Dams on the Basis of Fuzzy Logic
Authors:

Mostafa Yousefi Rad, Sina Shaffiee Haghshenas, Payam Rajabzade Kanafi and Sami Shaffiee Haghshenas
Abstract: The objective of this study is to survey the most appropriate way to protect body slope of the rockfill reservoir dams on the basis of fuzzy multiple criteria decision and analyze the Fuzzy Analytical Hierarchy Process (FAHP). In the present study, the reservoir dam of Shahr-e-Bijar, situated in Guilan province of Iran, has been studied. Also, for using the fuzzy analytical hierarchy process, eight important criteria in order to select the fittest way to protect body slope of the dam as well as five methods, namely, Riprap, Concrete facing, Asphalt concrete, Soil – Cement, and Geo-synthetic protection have been studied and analyzed. The fuzzy numbers used in this study are triangle fuzzy numbers. Moreover, Visual Basic Program has been used in calculations. Due to the result of the study, concrete protection is the best method among all other methods used to protect the body slope of the dams.
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Short Papers
Paper Nr: 11
Title:

Fuzzy Singleton Congestion Games
Authors:

Litsa Alexandra and Sbabou Samir
Abstract: In traditional game theory, the players attempt to maximize their utility functions. However, in real world there are many situations where payoffs have uncertainty and are fuzzy in nature. In this paper, we analyze fuzzy singleton congestion games with fuzzy payoff functions using tools from fuzzy set theory. We model this kind of games and we employ the ‘technique for order performance by similarity to ideal solution’ with fuzzy data in order to rank fuzzy payoffs, and consequently alternatives, with respect to multiple criteria. Based on this ranking we find possible solutions of these games which correspond to fuzzy Nash equilibria. Our method is adequate to model real-life situations, where players make more subtle decisions.
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Paper Nr: 12
Title:

Interactive Fuzzy Stochastic Multi-level 0-1 Programming through Probability Maximization
Authors:

Masatoshi Sakawa and Takeshi Matsui
Abstract: This paper considers multi-level 0-1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0-1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. An illustrative numerical example for a three-level 0-1 programming problem is provided to demonstrate the feasibility of the proposed method.
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Paper Nr: 16
Title:

Experience-based Fuzzy Control of an Anthropomimetic Robot
Authors:

Veljko Potkonjak, Nenad Bascarevic, Predrag Milosavljevic, Kosta Jovanovic and Owen Holland
Abstract: This paper aims to present a novel experience-based solution for a black-box control problem, applied to an anthropomimetic robot. The control method is tested on a point to point control problem of a multi-jointed robot arm. The model characteristics – dynamics, kinematics, and control parameters – are considered as unspecified, and therefore we deal with a machine learning approach that follows the cybernetic concept of black-box. The only available data of the system are those obtained from measuring inputs and outputs. The control algorithm involves two levels: feedforward and feedback. The main focus is, however, on feedback level where the algorithm for experience-based estimation of kinematic coefficients is combined with fuzzy logic control in order to relate the control inputs with the robot arm motion in the global frame.
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Paper Nr: 21
Title:

Generalized Hesitant Fuzzy Sets
Authors:

Bin Zhu
Abstract: The hesitant fuzzy set (HFS) is useful to deal with the situation that decision makers (DMs) assign several possible values to a fixed set. It is convenient to collect and deal with DMs’ preferences in group decision making. However, HFSs have the information loss problem and cannot tell DMs from each other in group decision making. In order to deal with these problems, we develop a generalized hesitant fuzzy set (GHFS) in this paper, which is an extension of the HFS.
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Paper Nr: 23
Title:

Similarity of Membership Functions - A Shaped based Approach
Authors:

Ana Tapia-Rosero, Antoon Bronselaer and Guy De Tré
Abstract: In this paper, we propose a method to group similar membership functions, each of them representing the opinion of an expert, to obtain a resulting membership function that represents alike opinions among a group. The similarity is based on the shape characteristics of membership functions used to represent the expert opinions on a specific criterion. There are several applications for the proposed method which include group decision making, suitability analysis and consensual processes. In each of these applications diverse points of view are present. The goals of the method are to detect similar membership functions, to establish a manner that allows the selection of representative opinions and to obtain a result membership function that represents a specific trend or a suitable concept for a group of similar membership functions. Our approach is based on soft computing techniques, considering expert preferences as a matter of degree, including a novel method to process similar opinions with more ease.
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Paper Nr: 24
Title:

A Comparison Study of Some Configurations of the Uninorm Morphological Edge Detector
Authors:

Manuel González-Hidalgo, Sebastià Massanet, Arnau Mir and Daniel Ruiz-Aguilera
Abstract: In this paper, we study the performance of the edge detector from the fuzzy mathematical morphology based on conjunctive uninorms. Several different pairs of uninorm and fuzzy implication (configurations) are considered in the fuzzy morphological gradient. The results are compared using an objective edge detection performance measure, the so-called Pratt’s figure of merit. To reinforce the analysis a K-means clustering algorithm has been applied to study the relation between the configurations and to determine which uninorm and implication have to be chosen to obtain an optimal edge detector. According to the analysis of the obtained results, the idempotent uninorm obtained using the classical negation, and its residual implication is the best configuration in this framework.
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Paper Nr: 25
Title:

Experiments and Design of an Inference Fuzzy System
Authors:

F. Benmakrouha, C. Hespel, E. Monnier and D. Quichaud
Abstract: The aim of this paper is to propose a criterion to estimate the design, from experimental data, of a fuzzy inference system, when data are sparse. This lack of data is important and may improve the generalisation ability of fuzzy systems (Isao Ishibuchi, 2002). Several methods have been proposed to obtain automatic fuzzy rules from sparse training data. In (Cruz Vega Israel, 2010), the authors first construct fuzzy rules from collect data. Then, they use kernel regressions for generate training data. Another technique used when classical inference methods produce sparse fuzzy rules is a diffusion procedure based on interpolation to initialize incomplete rules (Benmakrouha, 1997), (Glorennec, 1999), (Baranyi, 1996). Our method has the advantage of occuring before initialization step and therefore avoiding unfired rules which make difficult to produce an accurate output.
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Paper Nr: 36
Title:

Non-linear System Identification by a Fuzzy Takagi-Sugeno System Approach based on Reusable Fuzzified Inputs
Authors:

Cristian Guarnizo Lemus and Alejandro Restrepo Martinez
Abstract: An approach to fuzzy identification of discrete time nonlinear dynamical systems based on the Takagi-Sugeno (TS) model with a economical computation formulation is proposed. Number of rules and membership functions positions are fixed for all inputs. This allows to avoid the fuzzification proccess of delayed inputs. Rule base evaluation is avoided for delayed inputs by the Reusable Fuzzified Inputs approach. Consequent parameters are trained or estaimated using least squares approach. This method is intended to be trained in an off-line manner and used in programmable devices. Finally, simulations are performed on two diffrerent problems, the approach shows consistency, tracking of the output that vary with time and a high accuracy of the output estimate, properties requiered in control design applications.
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Paper Nr: 37
Title:

Interpretation of Semantically Tagged Data using Fuzzy Linguistic 2-Tuples
Authors:

Mohammed-Amine Abchir, Isis Truck and Anna Pappa
Abstract: We propose a natural language interface with interpretation of partially tagged semantically data in closed question/answering domain (geolocation) using fuzzy linguistic 2-tuples. The interface is a tool of configuration tasks such as alerts definition and modification, alerts messages, and other man-machine dialogue. The aim is to respond with precision to user's query, expressed in natural language, taking into account imprecision and vagueness. The combination of NLP techniques and fuzzy logic to interpret linguistic variables helps elicitation of business-level objectives avoiding useless and costly computation of middleware information. This paper introduces a methodology that deals with contextual fuzzy semantics in natural language interfaces.
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Paper Nr: 13
Title:

Illustrating the Difficulties of Zimmermann Method for Solving the Fuzzy Linear Programming by the Geometric Approach
Authors:

M. R. Safi and A. Razmjoo
Abstract: In this paper we first recall Zimmermann method and the Geometric approach for solving fuzzy linear programming problem. We show, by the geometric approach, Zimmerman method has some difficulties. Numerical examples are provided for illustrating the difficulties. Finally, the IZM algorithm for improving Zimmermann method is recalled.
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