Spatial Disorder in Complex Neuro-Fuzzy Dynamics

Neuro-Fuzzy Engineering for Spatial Information Processing

This paper proposes neuro-fuzzy engineering as a novel approach to spatial data analysis and for building decision making systems based on spatial information processing, and the development of this approach by the authors is presented in this paper. It has been implemented as a software environment and is illustrated on a case study problem. 1 Address correspondence to: Assoc. Prof. N.K. Kasab...

Transmission Dynamics of Malaria in Human Host: a Neuro-Fuzzy Approach

Neuro-fuzzy Systems D1.3 Neuro-fuzzy algorithms

See the abstract for Chapter D1. Relatively early in neural network research there emerged an interest in analyzing and designing layered, feedforward networks augmented by some formalism stemming from the theory of fuzzy sets. One of B2.3 the first approaches was the fuzzification of the binary McCulloch–Pitts neuron (Lee and Lee 1975). B1.2 Then, several researchers looked at a typical feedfo...

Hybrid Neuro-Fuzzy System for Control of Complex Plants

Arti cial Neural Networks (ANNs) and Fuzzy Systems (FS) are high parallel structures that consist of a large number of elementary nonlinear units (called neurons) fully interconnected. In this article we present a hardware implementation of ANNs combined with a DSP resulting in a powerful system used in control applications. The NN processes most of the control tasks, while the DSP performs sig...

Complex Neuro-Fuzzy Self-learning Approach to Function Approximation

A new complex neuro-fuzzy self-learning approach to the problem of function approximation is proposed, where complex fuzzy sets are used to design a complex neuro-fuzzy system as the function approximator. Particle swarm optimization (PSO) algorithm and recursive least square estimator (RLSE) algorithm are used in hybrid way to adjust the free parameters of the proposed complex neuro-fuzzy syst...