Building coal storage centre to settle the problem of power generation coal supply based on KPCA-SVRM

Abstract

This paper is established in electricity lines, and put forward the viewpoint that we can build coal storage center to settle the problem of power generation coal supply. Make the coal storage centre site selection by using KPCA (kernel principal component analysis) -SVRM (support vector regression machine), taking all factors into account, and making the advantage of the social division of labor specialization fully played. In KPCA-SVRM, the first step is to apply KPCA to SVRM for feature extraction. KPCA first maps the original inputs into a high dimensional feature space using the kernel method and then calculates PCA in the high dimensional feature space. These new features are then used as the inputs of SVRM to solve the site selection problem. By learning and training, we use the data of this subset to get the solution and find interrelationship of input and output by the SVRM. Practical examples are cited in this paper to illustrate the process.