7 The generation of membership functions for fuzzy systems is a challenging problem. We show that for Mamdani-type fuzzy systems with correlation-product inference, centroid defuzzi cation, and triangular membership functions, optimizing 9 the membership functions can be viewed as an identi cation problem for a nonlinear dynamic system. This identi cation problem can be solved with an extended ...

This paper presents alternative methods for producing fuzzy models for the fuzzy multiple heuristic ordering technique that we previously introduced for the construction of examination timetables. The effects of altering the rules within the fuzzy inference system were investigated. Four alternative rule 'tuning' approaches are described in detail and their results are presented and compared.

The generation of membership functions for fuzzy systems is a challenging problem. We show that for Mamdani-type fuzzy systems with correlation-product inference, centroid defuzzi%cation, and triangular membership functions, optimizing the membership functions can be viewed as an identi%cation problem for a nonlinear dynamic system. This identi%cation problem can be solved with an extended Kalm...

The Fuzzy hybridization technique for intelligent systems have become of research interests in a variety of research areas over the past decade. There are limitations faced by all popular fuzzy systems architectures when they are applied to applications with a large number of inputs (more than three). The present paper proposes a novel adaptive fuzzy inference system for multi-sensors mobile ro...

This paper presents the theory and design of interval type-2 fuzzy logic systems (FLSs) because of computational complexity of using general type-2 fuzzy set (T2FS) in type-2 fuzzy system. We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs; one that is based on a general inference formula for them. We introduce the concept of up...

This paper studies computational properties of fuzzy logic deduction and compares them with the standard inference methods. The principles of deduction in fuzzy logic are explained and algorithms for its computer realization are described. Basic algorithm has exponential complexity with respect to the number of antecedent variables, and in case of fuzzy observations we are able to improve its p...

The methods of ordinary least-squares regression (OLSR), fuzzy regression (FR), and adaptive network fuzzy inference system (ANFIS) are compared in inferring operating rules for a reservoir operations problem. Dynamic programming (DP) is used to provide the input-output data set to be used by OLSR, FR, and ANFIS models. The coefficients of an FR model are found by solving a linear programming (...

Purpose The motion control of unmanned ground vehicles is a challenge in the industry of automation. In this paper, a fuzzy inference system based on sensory information is proposed for the purpose of solving the navigation challenge of unmanned ground vehicles in cluttered and dynamic environments. Design/methodology/approach The representation of the dynamic environment is a key element for t...

Mamdani fuzzy models have always been used as black-box models. Their structures in relation to the conventional model structures are unknown. Moreover, there exist no theoretical methods for rigorously judging model stability and validity. I attempt to provide solutions to these issues for a general class of fuzzy models. They use arbitrary continuous input fuzzy sets, arbitrary fuzzy rules, a...

One of the tofu-producing companies in Kupang City is Bintang Oesapa. With Covid-19 pandemic,the factory needs to reconsider amount production by taking into account unpredictability ofdemand and resources minimize losses due excessive accumulation or shortages supplies. Indetermining production, Mamdani’s Fuzzy Inference System (FIS) can be used, whichis a method for analysis an uncertain syst...