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In the process of cost prediction modeling with support vector machine (SVM), the prediction accuracy is significantly impacted by the similarity between training samples and the predicted object. In traditional cost prediction modeling, the training data must be independent and identically distributed and every sample participating in training is treated equally. However, different samples owe the...
In the traditional feature selection, only a simple feature selection can be made, which will lead to the loss of information. In this paper, the requirement of weapon system economic analysis on the cost forecasting and the importance analysis of tactical and technical indicators were taken into account, moreover, considering the shortcomings of the traditional method of feature selection. A weighted...
Feature extraction is an important task before weapon system cost forecasting modeling, which affects the forecasting performance of the model. In this paper, feature extraction in the weapon system cost forecasting was studied. In regard to the mechanism of feature extraction and the good performance of support vector machine (SVM), principal components analysis (PCA) and kernel principal components...
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