This paper presents a modified feature ranking method on interclass separability based for fuzzy control application. Existing feature selection/ranking techniques are mostly suitable for classification problems. These techniques result in a ranking of the input feature or variables. Our modification exploits an arbitrary fuzzy clustering of the control output data. Using these output clusters ...

Opinion surveys are widely admitted as a valuable source of information which becomes complementary to the information extracted from data by machine learning techniques. This paper focuses on a challenging and still open problem which is related to how to handle properly the inherent uncertainty of human perceptions. Namely, we propose new ways to interpret and analyze fuzzy data coming out fr...

The paper presents a generalization of the Pittsburgh approach to learn fuzzy classification rules from data. The proposed approach allows us to obtain a fuzzy rule-based system with a predefined level of compromise between its accuracy and interpretability (transparency). The application of the proposed technique to design the fuzzy rule-based classifier for the well known benchmark data sets ...

This paper presents a way to combine outcomes of various studies in a meta analysis framework that can use the results of mixed methods and also provide query based output for intelligent decision making. We enhance the Qualitative Comparative Analysis by utilizing fuzzy logic programming to provide effective ways of combining output of various studies. The results from various studies are used...

In this document we carry out a comparative analysis of the application of Fuzzy Logic Controllers (hereinafter FLCs), Fuzzy Temporal Rules-Based Controllers (hereinafter FTRCs), Temporal Fuzzy Logic Controllers (hereinafter TFLCs) and Faded Temporal fuzzy Logic Controllers (hereinafter FTFLCs), to improve the adaptive distributed routing. To obtain a good knowledge base the controllers were ev...

In this document we cany out a comparative analysis of the reasoning strategies implemented in Fuzzy Logic Controllers (hereinafter FLCs) and Faded Temporal Fuzzy Logic Controllers (hereinafter FTFLCs). Starting from the problems associated to FLCs, we propose as a solution the use of FTFLCs. To improve the process of knowledge achievement in FTFLCs, it is introduced a mixed technique which com...

This paper proposes a fuzzy logic approach to allow qualitative symptoms that have been generated from order of magnitude qualitative simulation to be utilised as a fault detecting diagnostic system. The symptoms are interpreted as fuzzy rules and this allows numerical observations to be used as input to the symptoms and a ranking of faults as the output. The rule based approach results in a co...

Within the possibilistic approach to uncer­ tainty modeling, the paper presents a modal logical system to reason about qualitative (comparative) statements of the possibility (and necessity) of fuzzy propositions. We re­ late this qualitative modal logic to the many­ valued analogues MVS5 and MVKD45 of the well known modal logics of knowledge and be­ lief 55 and KD45 respectively. Completeness ...

measurement systems analysis (msa) has been applied in different aspect of industrial assessments to evaluate various types of quantitative and qualitative measures. qualification of a measurement system depends on two important features: accuracy and precision. since the capability of each quality system is severely related to the capability of its measurement system, the weakness of the two ...

Fuzzy sets are relatively new to social science. The first comprehensive introduction of fuzzy sets to the social sciences was offered by Michael Smithson (1987). However, applications were few and far between until the basic principles of fuzzy set analysis were elaborated through Qualitative Comparative Analysis (QCA; see Ragin 1987; 2000), an analytic system that is fundamentally settheoreti...