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This paper focuses on regression applications of the Support Vector Machine (SVM) in the process industry. The support vector regression machines are employed to build soft sensing models in the paper. Soft sensor modeling, in a sense, is a kind of regression problems in industrial processes. First we review the development history of the Vapnik Chervonenkis (VC) theory and SVM. And then, the basic...
Establishing the common pattern of the traditional Chinese medicine fingerprint signal is an important problem for the evaluation in herbal medicine field. This study deals with the application of support vector machine regression combined with discrete wavelet transform in creating the common pattern of fingerprint signal. The original signal was first decomposed to different scales by discrete wavelet...
Neural Network ensemble is a kind of method could significantly improve the generalization ability of the learning systems compare to the single network, it works by training a finite number of neural networks and then combining their results. Due to its generalization ability, network ensemble is widely used in regression and forecasting. The ways that realize the ensemble is numerous, one of them...
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