Power Investment Forecast Based on Classification and Regression Tree
Abstract
There are many factors affecting the scale of power network infrastructure investment, and the traditional grey theory model method does not consider multiple features at the same time on the forecast results. In this paper, we model the prediction of infrastructure investment as the classification and regression tree building hierarchical tree structure. The validity and reasonableness of the model are verified by the calculation experiment of power network infrastructure investment. Compared to the grey theory model, this method with higher accuracy takes into account a number of features that are highly relevant to infrastructure investment.
Keywords
Classification and regression tree, Grey correlation analysis, Infrastructure investment
DOI
10.12783/dtetr/ecar2018/26411
10.12783/dtetr/ecar2018/26411
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