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We propose a data mining approach to predict the wine's quality level in order to improve the quality of products for wine enterprises in this paper. A large dataset is considered and three regression techniques were applied. Through the comparison, we get the conclusion that the model established by neural network is more accurate and it can improve the quality of wine's production.
Development of mathematical models to predict the values of performance measure is important in order to have a better understanding of the machining process. Surface roughness is one of the most common performance measures in machining process and an effective parameter in representing the quality of machined surface. The minimization of the machining performance measures such as surface roughness...
Since the Neural Network (NN) with a Genetic Algorithm (GA) as a complement; are good optimization tools, we compare its performance with the Response Surface Methodology (RSM) that is generally used in the optimization of the process, in this case welding process. For the data used in the comparison, the results show that NN plus GA and RSM have a good results and very well performance, for identify...
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