Research on risk prediction algorithm for operation and maintenance data based on grey theory

Abstract

Abstract This paper proposes a risk prediction algorithm for power operation and maintenance data networks based on the grey theory, aiming at the real-time, healthy, and high stability requirements of power operation and maintenance data networks in work. By combining the entropy weight method to assign weight to risk indicators, the risk prediction of data networks in dynamic networks is achieved. By using two indicators of risk value and risk dispersion, the overall system is predicted for risk. Through experimental comparison, the prediction algorithm based on grey theory designed in this paper has a smaller error than existing prediction methods, which more scientifically realizes the risk prediction mechanism, ensures the stability of power operation and maintenance data, and ensures the reliable operation of the power grid.