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The most important task of power supply company is power grid operation management. Up to now, the development of China's power grid has entered an intelligent era, and the reason for this phenomenon lies in the formation of the new power grid operation and management system. In this case, enterprise leaders must put more energy into human resource management, otherwise the development of the company is difficult to be closely related to this period. Therefore, in order to realize the efficient and intelligent optimal allocation of human resources in power grid, this paper proposes a resource optimal allocation algorithm based on deep data generation and fuzzy neural network to predict the resource demand at a certain time in the future. The algorithm is based on fuzzy neural network for resource data mining and analysis, and on this basis, the network is refined by particle swarm optimization algorithm. The results of numerical experiments show that the prediction error of this algorithm for human resource demand of power grid enterprises is 0.13%, which is 2.84% lower than that of using fuzzy neural network only. Machine learning algorithm, which has been proved to have better overall performance.
Rongyu Zhang (Tue,) studied this question.