Abstract:

Evaluation of the performance of mobile network and its elements is the basis of network optimization. According to the problems existing in the applications of the methods applied at present, a new method based on dimension transformation and support vector machines was proposed. The steps were that, firstly, transforming the n related indicators to another n independent indicators, and secondly, using support vector machines (SVM) to model the transformed data. Theoretical analysis shows that this method can conquer the problems of back propagation（BP） neural network: overfitting,and the danger of getting stuck into local minima. The information loss occurring in the application of primary component analysis was avoided. Experimental results show that compared to BP neural network, the training process of support vector machines is more controllable, and the relative error of evaluation score based on support vector regression machines is smaller. Furthermore, the evaluation differences of the samples are maintained better.

Key words: back propagation neural network, primary component analysis, support vector machines, dimension transformation