The objective of this work was to develop an artificial neural network model to predict milk temperature of a locally fabricated solar milk pasteuriser, based on measures of error deviation from experimental data. A three-layer feed-forward neural network model based on back propagation algorithm was developed using the Neural Network Toolbox for MATLAB ® . The inputs of the model were ambient ...

This paper presents one of the soft computing methods, specifically the artificial neural network technique, that has been used to model the temperature dependence of dynamic mechanical properties and visco-elastic behavior of widely exploited thermoplastic polyurethane over the wide range of temperatures. It is very complex and commonly a highly non-linear problem with no easy analytical metho...

Reliability of nanodevices is expected to be a central issue with the advent of very-deep submicon devices and future single-electron transistors. We propose a new approach based on the assumption that a number of circuit-level devices are to be expected to fail. Artificial neural networks can be trained to resists to errors and be used for synthesizing fault-tolerant Boolean functions. The dev...

Our study is about feed-forward neural network’s learning method. Generally, the method of improving its learning is focused on learning rate and moment term. We focus on sigmoid functions. Sigmoid functions are used for converting input signal into output signal and adjusting connection weight of learning in feed-forward neural network. We change gradient of sigmoid functions and investigate o...

In this study, an Artificial Neural Network (ANN) approach is utilized to perform a parametric study on the process of extraction of lubricants from heavy petroleum cuts. To train the model, we used field data collected from an industrial plant. Operational conditions of feed and solvent flow rate, Temperature of streams and mixing rate were considered as the input to the model, whereas the flo...

Industrial pollution is often considered to be one of the prime factors contributing to air, water and soil pollution. Sectoral pollution loads (ton/yr) into different media (i.e. air, water and land) in Lagos were estimated using Industrial Pollution Projected System (IPPS). These were further studied using Artificial neural Networks (ANNs), a data mining technique that has the ability of dete...

We present in this paper a system of English handwriting recognition based on 26-point feature extraction of the character. Basically an off-line handwritten alphabetical character recognition system using multilayer feed forward neural network has been described in our work. Firstly a new method, called, 26-point feature extraction is introduced for extracting the features of the handwritten a...

accommodation of mechanism with human being’s physical characteristics creates the possibility of safe and efficient interaction between human being and robot. regarding the fact that amputation of a limb in human beings causes several mental, economical and social difficulties and problems, need to a substitute limb which has the most efficiency for the person after amputation is a vital need....

Skin recognition is used in many applications ranging from algorithms for face detection, hand gesture analysis, and to objectionable image filtering. In this work a skin recognition system was developed and tested. While many skin segmentation algorithms relay on skin color, our work relies on both skin color and texture features (features derives from the GLCM) to give a better and more effic...

In this work, response surface methodology (RSM) and artificial neural network (ANN) were used to predict the decolorization efficiency of Reactive Red 33 (RR 33) by applying the O3/UV process in a bubble column reactor. The effects of four independent variables including time (20-60 min), superficial gas velocity (0.06-0.18 cm/s), initial concentration of dye (50-150 ppm), and pH (3-11) were i...