In the present study, prediction of Alumina recovery efficiency (A.R.E), the amount of produced red mud (A.P.R), red mud settling rate (R.S.R) and bound-soda losses (B.S.L) in Bayer process red mud has been carried out for the first time in the field. These predictions are based on Lime to bauxite ratio and chemical analyses of bauxite and lime as Bayer process feed materials. Radial basis func...

The goal of this paper is to compare and analyze the forecasting performance of two artificial neural network models (i.e., MLP (multi-layer perceptron) and DNN (deep neural network)), and to conduct an experimental investigation by data flow, not economic flow. In this paper, we investigate beyond the scope of simple predictions, and conduct research based on the merits and data of each model,...

Procedures using Artificial Neural Networks (ANN) are developed for characterizing square microstrip antennas. A Multi-Layer Perceptron (MLP) is used to find out the resonant frequency of the antennas. Same ANN is used to accomplish the task of obtaining different important antenna characteristics like gain, return loss and bandwidth of operation at once. The developed ANN is tested experimenta...

This paper reports a comparative study between continuous hidden Markov model (CHMM) and artificial neural network (ANN) on text dependent, closed set speaker identification (SID) system with Thai language recording in office environment. Thai isolated digit 0-9 and their concatenation are used as speaking text. Mel frequency cepstral coefficients (MFCC) are selected as the studied features. Tw...

Artificial Neural Network (ANN) is an effective technique of Soft Computing can model ComputerAided Diagnosis (CAD) system efficiently. CAD system is an essential for the prediction of Malignancy in Cervical Cancer. Cervical Cancer can be cured if it is diagnosed in early stages. Hence, for the effective screening of cancer lesions in the Cervical cell images which are captured using Pap smear ...

contamination of water by heavy metals is a global problem. nowadays everybody knows that heavy metal ions consist of iron, lead, manganese, zinc, copper, cadmium, and nickel and so on they are common contaminants in wastewater and known to be toxic and carcinogenic that lead to many problems for human and water environment. in this research, experiments have been performed in the batch system ...

This paper describes artificial neural network (ANN) based prediction of theresponse of a fiber optic sensor using evanescent field absorption (EFA). The sensingprobe of the sensor is made up a bundle of five PCS fibers to maximize the interaction ofevanescent field with the absorbing medium. Different backpropagation algorithms areused to train the multilayer perceptron ANN. The Levenberg-Marq...

The artificial neural networks (ANN) are the learning algorithms and mathematical models, which mimic the information processing ability of human brain and can be used to non linear and complex data. The aim of this study was to compare artificial neural network and regression models for prediction of body weight in Raini Cashmere goat. The data of 1389 goats for body weight, height at withers ...

The paper presents an S-Transform based multilayer perceptron neural network (MLP) classifier for the identification of power quality (PQ) disturbances.The proposed method is used to extract the three input features (Standard deviation, peak value and variances) from the distorted voltage waveforms simulated using parametric equations. The features extracted through S-transform are trained by a...

Neural network process modelling needs the use of experimental design and studies. A new neural network constructive algorithm is proposed. Moreover, the paper deals with the influence of the parameters of radial basis function neural networks and multilayer perceptrons network in process modelling. Particularly, it is shown that the neural modelling, depending on learning approach, cannot be a...