Prediction and Assessment of Investment Income of Power Grid Technology Projects

Abstract

Aiming at the problem of investment prediction of power grid technology projects, an investment income prediction model based on grey model is constructed. Selecting the relevant statistical data of a power grid company from 2015 to 2019, using the grey correlation analysis method to extract three factors that have a greater impact on the investment income of science and technology projects, and establish a GM(1, 4) model. Using the error compensation method based on artificial neural network combined with GM(1, 4) model, the investment income of a power grid company’s power grid technology project from 2020 to 2024 is predicted. Aiming at the problem of how to assess the power grid technology projects, the weight of each index is determined by the analytic hierarchy process, and establish a scoring model based on the weight of each index. The evaluation scores of the power grid company’s technology projects from 2015 to 2019 were calculated, and then the corresponding evaluation scores were obtained based on the predicted value of investment income in the next five years, which provided a basis for judging the investment development trend of technology projects.