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Support vector machine (SVM) which overcomes the drawbacks of neural networks has been widely used for forecasting and pattern recognition in recent years. In the study, the proposed SVM model is applied to pest degree forecasting of rice stem borer, and the structure of SVM forecasting system of pest degree is presented. The real data sets are used to investigate its feasibility in pest degree forecasting...
Abstract A new method of using Vis/NIR spectroscopy technique to identify the varieties of red wines was studied. Through comparing modeling performance built by different amounts of independent components, 20 independent components (ICs) extracted by independent components analysis (ICA) were employed as the inputs of the BP neural networks and were consider to be important parameter for calibration...
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