In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

In this paper, a TSK-type recurrent fuzzy network (TRFN) structure is proposed. The proposal calls for a design of TRFN by either neural network or genetic algorithms depending on the learning environment. Set forth first is a recurrent fuzzy network which develops from a series of recurrent fuzzy if–then rules with TSK-type consequent parts. The recurrent property comes from feeding the intern...

In this chapter the problem of identifying events in dynamic processes (e.g. faults, anomalous behaviours, etc.) is tackled with soft computing techniques aimed at the classification of the process transients generated by such events. A review of previous work is followed by a discussion of several alternative designs and models which employ both fuzzy and neural systems. These have been develo...

this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...

In this paper we present an approach for generation and initialization of fuzzy neural networks (FNN) from data. Fuzzy neural networks are concept that integrates some features of the fuzzy logic and the artificial neural networks theory. Based on analysis of several different fuzzy neural networks models, uniform representation method is presented, and two basic types are identified: FNN based...

Over the last decade or so, significant advances have been made in two distinct technological areas: fuzzy logic and computational neutral networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. Also, it provides a mathematical morphology to emulate certain perceptual and lingui...