This chapter discusses several issues related to the design of linguistic models with high interpretability using fuzzy genetics-based machine learning (GBML) algorithms. We assume that a set of linguistic terms has been given for each variable. Thus our modelling task is to find a small number of fuzzy rules from possible combinations of the given linguistic terms. First we formulate a threeob...

In this paper a multi - objective linear fractional programming problem with the fuzzy variables and vector of fuzzy resources is studied and an algorithm based on a parametric approach is proposed. The proposed solving procedure is based on the parametric approach to find the solution, which provides the decision maker with more complete information in line with reality. The simplicity of the ...

Fuzzy multi-objective linear programming (FMLOP) problem has its vast applications in the field of science and engineering. Many authors proposed different method to solve those problems. In this paper, FMOLP problem in which both technological coefficient and resources are fuzzy with linear membership function was studied and a novel approach was proposed to solve the above problem using the t...

We examine several formulations of fuzzy rule selection for the design of fuzzy rulebased classification systems in our twostage approach. The first stage is heuristic rule extraction where a large number of candidate rules are extracted. The second stage is evolutionary rule selection where fuzzy rule-based systems are constructed by choosing a small number of candidate rules. Rule selection i...

It takes two design goals as different game players and design variables are divided into strategy spaces owned by corresponding game player by calculating the impact factor and fuzzy clustering. By the analysis of behavior characteristics of two kinds of intelligent pigs, the big pig’s behavior is cooperative and collective, but the small pig’s behavior is noncooperative, which are endowed wit...

A new algorithm is proposed to learn fuzzy partitions with a high interpretability degree. The set of input variables, the number of linguistic terms per variable, and the type (triangular or trapezoidal) and parameters of the membership functions are learnt by means of a meta-algorithm that uses a simple learning method to generate a fuzzy rule set from the derived fuzzy partitions. Interpreta...

In this paper, a multi-objective intuitionistic fuzzy linear fractional programm ing problem is discussed with two different methods namely Kanti Swarup’s Fractional algorithm and weighting factor method in which the constraints are triangular intuitionistic fuzzy number. The optimal solutions are verified for the proposed methods. Numerical examples are provided to check the feasibility of the...

This article addresses a special class of non-linear programming problems, viz., linear fractional problems having multiple objectives. In solving the real-life optimization ambiguity and hesitation in decision are inherent ever-present, therefore, it is perfectly viable to formulate solve these models using intuitionistic fuzzy environment. The purpose this study propose simple computationally...