Design of Human Resource Optimal Allocation Model for Electric Power Construction Enterprises Based on Machine Learning

Electric power construction enterprises have the characteristics of huge capital occupation, long project cycle and complicated management interface. Although the project management theory has been widely used in the construction of electric power enterprises in my country, there are still many problems. Human resource planning, as an important part of enterprise human resource management, is the extension of enterprise strategy in human resource management. In order to optimize the resource management process, reduce business workload, and improve work efficiency, the introduction of machine learning methods to realize the functions of human resource management system can reduce business workload, thereby improving work efficiency and system performance [1]. The model is designed and implemented by applying machine learning technology to human resource management system. Build a human resource demand model system that can control the total amount of labor, labor allocation, optimize the workforce, and standardize labor strategies, and find out the corresponding relationship and law between the development of the power grid enterprise workforce and the scale of business growth, production efficiency and economic benefits. Realize the forecast of the quantity, structure and quality of human resource demand for the strategic development of the enterprise, and formulate an effective recruitment strategy in combination with the supply of internal and external talent markets to optimize the allocation of human resources. For this purpose, it can accurately predict human resource needs, provide decision support for enterprise human resource development planning, provide reliable human resource guarantee for the realization of enterprise strategic goals, and lay a solid human resource foundation for the sustainable and healthy development of the enterprise.