Research on Optimization Path of Intelligent Pension Industry Based on Intelligent Fusion Algorithm of Multisource Information

Abstract

Accurate quantitative evaluation of the supervision effect of the smart pension industry can reduce the cost of social pension. The traditional methods cannot effectively classify the regulatory risk levels of the smart pension industry. Therefore, this paper proposes a multisource information intelligent fusion algorithm based on the intelligent pension industry optimization path research. Firstly, we establish the principal model of the supervision effect system of the intelligent elderly care industry optimization path and describe the risk level of the supervision effect from different levels. We build the intelligent service platform of the intelligent elderly care training, calculate the weight vector of the supervision risk of the optimization path at all levels, and determine the attribute type of the supervision effect at all levels. Finally, we calculate the maximum influence value of the supervision effect of the intelligent elderly care industry optimization path and use this value to complete the quantitative evaluation of its supervision effect. Simulation results show that the proposed method can evaluate the regulatory effect of smart pension industry and improve the precision of the regulatory effect of smart pension industry effectively.