Research on the Operation and Optimisation of Smart Power Plant System Based on Artificial Intelligence

This thesis constructs an intelligent power big data algorithm selection and evaluation system by investigating the evaluation and selection methods of supervised machine learning algorithms related to power big data. Based on the big data background of artificial intelligence, in order to make the system more suitable for the needs of power big data analysis, this paper needs to carry out an artificial pre-assessment of the mainstream machine learning algorithms to determine the key machine learning algorithms for power big data, and for this reason, it is necessary to construct a machine learning algorithm index system. The process of constructing the indicator system is to select a number of interrelated statistical indicators to form the indicator system. The principles that should be followed in selecting the indicators are the principle of purpose, the principle of comprehensiveness, the principle of feasibility, the principle of stability, the principle of coordination and the principle of integration. The principle of coordination and the principle of integration.