Fuzzy models to recognize consumer preferences were developed as part of an automated inspection system for biscuits. Digital images were used to estimate physical features of chocolate chip cookies including size, shape, baked dough color, and fraction of top surface area that was chocolate chips. Polls were conducted to determine consumer ratings of cookies. Four fuzzy models were developed t...

This paper describes the VHDL modeling of temperature controller based on fuzzy logic intended for industrial application. The system is built of four major modules called fuzzification, inference, implication and defuzzification. The composition method selected for the fuzzy model is the Max-Min composition while the Mamdani Min operator was chosen as the implication method. Each module is mod...

This paper implements a Neuro-Fuzzy (FNN) approach to autonomously navigate a car-like robot in an unknown environment. The applied technique allows the robot to avoid obstacles and locally search for a path leading to the goal after learning and adaptation. It is based on two Fuzzy Artmap neural networks, a Reinforcement trial and error neural network and a Mamdani fuzzy logic controller (FLC)...

The aim of the paper is to demonstrate the neuro-fuzzy support of knowledge management in social regulation. Knowledge, defined as human capability of making data and information useful for decision making processes, could be understood for social regulation purposes as explicit and tacit. Explicit knowledge relates to the community culture indicating how things work in the community based on s...

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...

Information on the future state of traffic flow provides a solid foundation for the efficient implementation of traffic control and guidance. The prediction approaches based on fuzzy logic theory is of great interests, because the rule-based inference is similar to the way humans process casual relations and fuzzy linguistic variables provide a natural way to deal with uncertainties. This paper...

The majority of the research work on fuzzy PID controllers focuses on the conventional two-input PI or PD type controller proposed by Mamdani (1974). However, fuzzy PID controller design is still a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. This paper investigates different fuzzy PID controller structures, including the Mamdani-type cont...

one-third of the people with an age over twenty have some signs of degenerated discs. however, in most of the patients the mere presence of degenerative discs is not a problem leading to pain, neurological compression, or other symptoms. this paper presents an interval type-2 fuzzy hybrid rule-based system to diagnose the abnormal degenerated discs where pain variables are represented by interv...

This paper presents a novel hybridization of the fuzzy logic, the neural network and the coevolutionary algorithm for building a fuzzy-neural system (or a Mamdani fuzzy system) from data. The novel hybridization uses the coevolution of many species, and proposes the coevolution of groups of similar species, both for the optimization of the structure of the fuzzy-neural network. In the fuzzy-neu...