production of several yeast products occur in presence of mixtures of monosaccharides. to study effect of xylose and glucose mixtures with system aeration and nitrogen source as the other two operative variables on xylitol production by pichia guilliermondii, the present work was defined. artificial neural network (ann) strategy was used to athematically show interplay between these three contr...

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...

Water Quality plays an important role in attaining a sustainable aquaculture system, its cumulative effect can make or mar the entire system. The amount of dissolved oxygen (DO) alongside other parameters such as temperature, pH, alkalinity and conductivity are often used to estimate the water quality index (WQI) in aquaculture. There exist different approaches for the estimation of the quality...

Linear regression is widely used in flood quantile study that consists of meteorological and physiographical variables. However, linear does not capture the complex nonlinear relationship between predictor target It rare to find a hydrological application using group method data handling (GMDH) model, artificial bee colony (ABC) algorithm, ensemble technique, precisely predicting ungauged sites...

Residential sector is one of the energy-consuming districts countries that causes CO2 emission in large extent. In this regard, must be considered energy policy making related to reduction and other greenhouse gases. present work, residential three countries, including Indonesia, Thailand, Vietnam Southeast Asia, are discussed modeled by employing Group Method Data Handling (GMDH) Multilayer Pe...

This paper presents the application of six nonlinear ensemble architectures to forecasting the foreign exchange rates in the computational intelligence paradigm. Intelligent techniques such as Backpropagation neural network (BPNN), Wavelet neural network (WNN), Multivariate adaptive regression splines (MARS), Support vector regression (SVR), Dynamic evolving neuro-fuzzy inference system (DENFIS...

the objective of this paper is to develop an artificial neural network (ann) model which can beused to predict temperature rise due to climate change in regional scale. in the present work data recorded overyears 1985-2008 have been used at training and testing steps for ann model. the multilayer perceptron(mlp) network architecture is used for this purpose. three applied optimization methods a...

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...

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...