PHP Architecture Optimization of Electric Power Service Government Scientific Decision-Making Platform

This study focuses on PHP architecture optimization of electric power service government scientific decision-making platform. The novelty of the study contains the following aspects. (1) For the service interface test automation tool, the model-driven testing is an important strategy to realize automated testing. Testers use the model to abstractly describe the system under test, and generate the effective test cases based on the model to realize test automation. A novel test method is designed to improve the testing performance. (2) The PHP architecture is optimized to serve as the efficient tool. (3) In terms of simulation decision-making, some studies have learned from the interaction process between the agent and the environment through reinforcement learning models, these ideas are proposed for the electric power service government scientific decision-making. Then, through the testing under different scenarios, the performance of the designed model is validated and the future study plan is also marked in the final section.