Research on the Construction of Service Operation Indicators and Indicator Calculation Methods Based on Artificial Intelligence

The research on indicator construction and calculation methods is critical in service operation indicators, however it has an issue with erroneous performance positioning. The typical Particle swarm arithmetic is unable to address the inaccurate calculation and positioning issue in service operation indicators, and the result is insufficient. As a result, a Artificial intelligence-based construction of service operation indicators and the research of indicator calculation method is provided, and construction of service operation indicators and the research of indicator calculation method is assessed. To begin, the neural network theory is used to discover the influencing elements, and the indicators are split based on the research on indicator construction and calculation method’s needs to decrease interference factors in the research on indicator construction and calculation methods. The neural network theory is then used to create a Artificial intelligence research on indicator construction and calculation methods scheme, and the outcomes of the research on indicator construction and calculation methods are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Artificial intelligence outperforms the standard Particle swarm arithmetic in terms of research on indicator construction and calculation methods accuracy and time of influencing variables.