i DECLARATION No portion of the work referred to in this dissertation has been submitted in support of an application for another degree or qualification of this or any other university or other institution of learning. ii ABSTRACT Real world problems are described by non-linear and chaotic processes which makes them hard to model and predict. The aim of this dissertation is to determine the st...

In present study, a three-step multi-objective optimization algorithm of cyclone separators is catered for the design objectives. First, the pressure drop (Dp) and collection efficiency (h) in a set of cyclone separators are numerically evaluated. Secondly, two meta models based on the evolved Group Method of Data Handling (GMDH) type neural networks are regarded to model the Dp and h as the re...

In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The new improved GMDH is then used to predict currency exchange rates: the US Dollar to the Euros. The performance of the hybrid GMDHs are compared with that of the conventional GMDH. Two performance mea...

Prediction of the production rate of the cutting dimensional stone process is crucial, especially when chain saw machines are used. The cutting dimensional rock process is generally a complex issue with numerous effective factors including variable and unreliable conditions of the rocks and cutting machines. The Group Method of Data Handling (GMDH) type of neural network and Radial Basis Functi...

In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...

The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between...

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and perturbed by the variation rotor resistance load changes. system has two stages. identification stage, group method data-handling (GMDH) neural network (NN) was designed online modeling IM. GMDH-NN applied to compensate impacts disturbances uncertainties. stability shown Lya...

the objective of this study is development of driver’s sleepiness using visually evoked potentials (vep). vep computed from eeg signals from the visual cortex. we use the steady state veps (ssveps) that are one of the most important eeg signals used in human computer interface systems. ssvep is a response to visual stimuli presented. we present a classification method to discriminate between cl...

doi:10.1111/j.1742-4658.2004.04475.x Many organelle enzymes coded for by nuclear genes have N-terminal sequences, which directs them into the organelle (precursor) and are removed upon import (mature). The experiments described below characterize the differences between the precursor and mature forms of watermelon glyoxysomal malate dehydrogenase. Using recombinant protein methods, the precurso...