The paper shows and includes targeted supervision of optimizing machining parameters. Material Removal Rate surface roughness being integral to efficacy any workpiece , simulation based modeling helps in failure mitigation.Thepotential ANN-GA mathematical approach for prediction optimization MRR AL 6061 a analysis statistical study has been discussed. computational model between the desired out...

This paper reports an intelligent approach for process modeling and optimization of electric discharge machining (EDM). Physics based process modeling using finite element method (FEM) has been integrated with the soft computing techniques like artificial neural networks (ANN) and genetic algorithm (GA) to improve prediction accuracy of the model with less dependency on the experimental data. A...

Overwhelming majority of neurobiologists' research efforts has recently revealed findings about common increasingly sophisticated role adopted by Artificial Neural Networks (ANN s ). This role applied commonly for systematic realistic modeling of interdisciplinary disciplines incorporating neuroscience, education, and cognitive sciences. Accordingly, ANN s Models vary in relation to the nature ...

INTRODUCTION Workforce is one of the pillars of development in any country. Therefore, the workforce's health is very important, and analyzing its threatening factors is one of the fundamental steps for health planning. This study was the first part of a comprehensive study aimed at comparing the fitting methods to analyze and model the factors threatening health in occupational injuries. MET...

BACKGROUND Wax esters are important ingredients in cosmetics, pharmaceuticals, lubricants and other chemical industries due to their excellent wetting property. Since the naturally occurring wax esters are expensive and scarce, these esters can be produced by enzymatic alcoholysis of vegetable oils. In an enzymatic reaction, study on modeling and optimization of the reaction system to increase ...

    Drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. Identification of resistant phenotype is very important because it can lead to effective treatment plan. There is an interest in developing classifying models of resistance phenotype based on the multivariate data. We have investigated a vibrational spectroscopic approach in order to characterize a...

Introduction: In Processes Modeling, when there is relatively a high correlation between covariates, multicollinearity is created, and it leads to reduction in model's efficiency. In this study, by using principle component analysis, modification of the effect of multicolinearity in Artificial Neural Network (ANN) and Logistic Regression (LR) has been studied. Also, the effect of multicolineari...

Cryptocurrencies are currently traded worldwide, with hundreds of different currencies in existence and even more on the way. This study implements some statistical machine learning approaches for cryptocurrency investments. First, we implement GJR-GARCH over GARCH model to estimate volatility ten popular cryptocurrencies based market capitalization: Bitcoin, Bitcoin Cash, SV, Chainlink, EOS, E...

The use of art ificial neural network (ANN)modeling for prediction and forecast ing variables in water resources engineering are being increasing rapidly Infrastructural applicat ions of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters indifferent types of neural networks used in water resources engineering have been report...