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Engineering optimization is an actual goal in manufacturing and service industries. In the tutorial we represented the concept of traditional parametric estimation models (Factorial Design (FD) and Central Composite Design (CCD)) for searching optimal setting parameters of technological processes. Then the 2D mapping method based on Auto Associative Neural Networks (ANN) (particularly, the Feed Forward...
The goal of this paper is to represent the feed forward bottle neck neural network (FFBN NN) mapping technique in comparison with traditional statistical method like Factorial Design (FD). Application of both methods provides more information about studied process and enable to establish certificate limits more affectively reaching to best quality and selecting the less cost processes. The represented...
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