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Network intrusion detection research work that employed KDDCup 99 dataset often encounters challenges in creating classifiers that could handle unequal distributed attack categories. In such cases, classifier could not effectively learn the characteristics of rare categories, which will lead to a poor detection rate of rare categories. The efficiency of intrusion detection is mainly determined by...
A way of combining SVM(Support Vector Machine) with Supervised Subset Density Clustering is proposed in this paper. How to minimize the training set of SVM by means of clustering is researched. Original center positions are of great importance to clustering accuracy. However the traditional clustering center choosing algorithm doesn't work properly when the same kind of samples aren't closely-spaced...
In this study, the prediction of total power of agricultural machinery is investigated using artificial neural networks (ANN). This paper presents an accurate model by training with value of the total power of agricultural machinery from 1990 to 2003. Values of total power of agricultural machinery from 2004 to 2007 are predicted, predicted results and the ANN are in close agreements with errors less...
The continuous deterioration of ground water quality is one of the important factors that affect development of national economy and society. Based on the DE-BP (Back Propagation-Differential Evolution) neutral network, the predicting model of ground water quality is presented. The precision of the model is checked using the monitoring data in Zhangjiakou area. The comparisons between the predicted...
The continuous decline of ground water level is one of the important factors that affect development of national economy and society. Based on the DE-BP (back propagation-differential evolution) neutral network, the predicting model of ground water level is presented. The precision of the model is checked using the monitoring data in Zhangjiakou area. The comparisons between the predicted results...
Using the characteristic of nonlinear function approach of CMAC neural network in cluster node, a novel model of comprehensive calibration, which aiming to improve the static state output characteristic of sensor nodes, was presented. Correction model of sensor nodes and comprehensive calibration model of cluster node were set up. The arithmetic is demonstrated, according to the simulation results,...
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