Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

For the present work the parameter to be optimised selected is material removal rate that is optimised by using selected combination of machining parameters by using

In this work a comparative study of the bilinear dynamic identification of a helicopter blade aeroelastic response is carried out using artificial neural networks is presented.. Two

In this study it is compared predictability of various prediction models such as discriminant analysis and artificial neural networks using usually in literature.. For this

A mathematical model functionally relating process parameters and operating parameters of a wire cut electric discharge machine (WEDM) is developed incorporating Artificial

Relative contribution, obtained by the method of Garson (1991), of the colorimetric parameters in the input layer to predict the vitamin A level using artificial neural

The comparison of classification in artificial and fuzzy neural networks technique has been conducted to separate classes of forest from non-forest using SPOT satellite

(2007) carried out the optimization of a finish hard turning process for the machining of D2 steel with ceramic tools using neural network models to predict the surface roughness

Thus, this study aims to assess the use of Artificial Neural Networks (ANN) to predict particleboard quality, using as input variables the density (quantitative variable) and