During the development of the power industry

there exist acts of illegal electricity theft

which cause significant economic losses to the national power system. To curb illegal electricity theft and ensure the safe and stable operation of the national power grid

this paper analyzes the application of intelligent anti-electricity-theft technologies in electricity inspection of power automation systems. By sorting out the types and characteristics of electricity theft

this paper constructs an intelligent anti-electricity-theft technology model integrating machine learning and neural networks. Relying on this model

the accurate analysis and identification of electricity theft behaviors are realized

providing support for the anti-electricity-theft work of power enterprises. This paper also designs an anti-electricity-theft system architecture

conducts in-depth analysis of electricity theft detection data

and provides theoretical support for the optimization of anti-electricity-theft technologies.