A Critical Value-based Early Warning Algorithm for Systematic Personal Risk in Power Supply Companies

The conventional human risk early warning algorithm for power supply enterprise system mainly uses the Z-Stack Hough multi-source centralized sensing protocol to divide the early warning threshold, which is vulnerable to the random changes of signals, resulting in poor early warning performance indicators. Therefore, a critical value based human risk early warning algorithm for power supply enterprise system is proposed. That is to extract the characteristics of the systematic personal risk early warning of power supply enterprises, and use the critical value to generate the optimization process of the systematic personal risk early warning algorithm of power supply enterprises, thus realizing the personal risk early warning. The experimental results show that the designed systematic personal risk early warning algorithm for power supply enterprises has good indicators, reliability and certain application value, and has made certain contributions to promoting the sustainable development of power supply enterprises and realizing digital security transformation.