This chapter describes the intersection of two areas of artificial intelligence research, genetic algorithms and neural networks. The chapter has six main sections. The first describes the motivation for this research, which is followed by a gentle introduction to the basic principles of genetic algorithms. The third section deals with the application of genetic algorithms to conventional neura...

A new mathematical modeling technique known as soft computing is showing promise in modeling complex human behaviors. This paper will discuss the theoretical concepts of a soft computing technique, neurofuzzy systems. This technique has direct application to behavioral modeling of synthetic forces. Furthermore, the paper will present a specific experiment and modeling of the human operator’s be...

Probabilistic distance functions, including several variants of value difference metrics, minimum risk metric and ShortFukunaga metrics, are used with prototype-based rules (P-rules) to provide a very concise and comprehensible classification model. Application of probabilistic metrics to nominal or discrete features is straightforward. Heterogeneous metrics that handle continuous attributes wi...

The observational study of the determinants of Plasma Beta-Carotene Levels through the investigation of the relationship between personal characteristics and plasma concentrations of beta-carotene has been examined by the various multivariate analysis techniques using the neurofuzzy systems with applying the various reduced data sets without losing any significant meaning comparing to the origi...

A solution to get the problem off, have you found it? Really? What kind of solution do you resolve the problem? From what sources? Well, there are so many questions that we utter every day. No matter how you will get the solution, it will mean better. You can take the reference from some books. And the adaptive modelling estimation and fusion from data a neurofuzzy approach is one book that we ...

Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of M...

In this paper, two CI techniques, namely, single multiplicative neuron (SMN) model and adaptive neurofuzzy inference system (ANFIS), have been proposed for time series prediction. A variation of particle swarm optimization (PSO) with co-operative sub-swarms, called COPSO, has been used for estimation of SMN model parameters leading to COPSO-SMN. The prediction effectiveness of COPSO-SMN and ANF...

Long distance AC transmission is often subject to stability problems, which limits the transmission Capability. Large interconnected power systems often suffer from weakly damped swings between synchronous generators and subsystems. This paper studies the comparative performance of SSSC and UPFC for the improvement of transient stability and damping of power swings of a multi-machine power syst...

A neural network can approximate a function, but it is impossible to interpret the result in terms of natural language. The consolidation of neural networks and fuzzy logic in neurofuzzy models provides learning as well as readability. This paper aims at modeling the input-output relationship with fuzzy IF-THEN rules by using fuzzy clustering technique. The main difference between fuzzy cluster...

In the field of diabetic retinopathies attention has been recently focused on the problem of obtaining an accurate diabetic ocular diagnosis. In this paper a contribution in the detection of diabetic symptoms using contrast enhancement of fundus images is proposed by synthesizing an “ad hoc” neurofuzzy system. A fuzzy technique is considered to develop a suitable coding of fuzzy rules. A sparse...