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This paper discusses the development and application of a decomposition neural network rule extraction algorithm for nonlinear regression problems, the algorithm is called the piece-wise linear artificial neural network or PWL-ANN algorithm. Rules in the form of linear equations are generated by approximating the sigmoid activation functions of the hidden neurons in an artificial neural network (ANN)...
For today the unit neural networks are widely used to solve various problems. In this regard the issue of developing learning algorithm that would be able to optimize the structure of neural networks dynamically is very important. The existence of such a method would allow the researcher to get the structure of the neural network that would be best-answered domain and available input data quickly.
To bridge the semantic gaps between the low-level image visual features and the high-level emotional semantics, the paper describes image features using texture and completes the semantic mapping through BP neural network. On the premise of keeping the accuracy of classification unchanged, the trained feedforward neural network is pruned using RX algorithm. Finally, the rules of IF-THEN which can...
The researches on feature selection play a very important role in the area of classification. In this paper, we introduce a heuristic wrapper method: Classification Contribution-Ratio Based Selection (CCRS). Using RBF neural network as a classifier, we did our experiments on a data set of 74 features extracted from 517 Chinese folk songs which come from 10 regions. The results show that Root Mean...
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