Elastic Resource IT Analysis Technology for Distribution Station Area Based on Genetic Optimization Algorithm

In view of the limitations of the traditional selection and ranking algorithm in the elastic resource IT analysis technology for distribution station area, a flexible resource IT analysis technology scheme based on genetic optimization algorithm was proposed. Firstly, the influencing factors is accurately located through the population optimization theory, and the indicators is reasonably divided to reduce interference, and the genetic optimization algorithm is used to construct the technical scheme of elastic resource IT analysis. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional selection and ranking algorithm in terms of the accuracy of elastic resource IT analysis technology and the processing time of influencing factors, and has obvious advantages. The elastic resource IT analysis technology plays an extremely important role in the distribution station area, which can accurately predict and optimize the growth characteristics and product generation of the distribution station area. However, the traditional selection and ranking algorithm has certain limitations in solving the simulation problem of IT analysis, especially when dealing with complex problems. In this paper, this paper proposes a technical scheme for the analysis of elastic resources based on genetic optimization algorithm to better solve this problem. In this scheme, the influencing factors is accurately located through the population optimization theory, so as to determine the division of indicators, and the genetic optimization algorithm is used to construct the scheme. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on genetic optimization algorithm can better solve the limitations of the traditional selection and ranking algorithm and improve the simulation accuracy and efficiency in the elastic resource IT analysis technology for the distribution station area.