Investment capacity prediction of Power Grid Enterprise based on Self-organizing Data Mining Technology

Abstract

With the expansion of power grid investment demand and investment scale, the research on power grid enterprises' investment capacity is particularly important. This paper expounds the basic principle of self-organizing Data Mining technology, and on this basis, establishes the GMDH model of power grid enterprises' investment capacity prediction, describes the process of establishing the model in detail. Then, the indicator system of power grid enterprises' investment capacity factors is constructed, and the GMDH model is used to forecast and analyze the investment capacity of HM Grid Company based on the data of factors from 2008 to 2020. The research results show that the GMDH model of grid enterprise investment capacity prediction is robust, not only can avoid artificial interference, self-organized selection of influencing factors, and meet the requirements of objectivity and authenticity, but also has a good prediction performance, high prediction accuracy, and more reliable prediction results, which provides new thoughts and approaches of measuring the investment capacity of grid enterprise.