Construction of an Intelligent Evaluation Model of Yield Risk Based on Empirical Probability Distribution

In order to improve the accuracy of yield risk evaluation, an intelligent evaluation model of yield risk based on empirical probability distribution is constructed. The dimensionality reduction method of risk factor based on principal component analysis is adopted. After adjusting the multiple data dimensions of risk factors that affect the rate of return to a unified dimension, the cluster-based evaluation index screening method is used to build the evaluation index set that best reflects the risk of the rate of return; The index weight vector equation method based on entropy weight and information entropy is used to set the evaluation index weight. Through the comprehensive evaluation model based on the empirical probability distribution of risk indicators, the empirical probability distribution information of risk indicators at all levels is analyzed, and the risk level of yield is intelligently evaluated. The research structure shows that the model can effectively evaluate the level of return risk and provide an effective reference for preventing and controlling investment return risk.

@article{Yanru2023,
  title     = {Construction of an Intelligent Evaluation Model of Yield Risk Based on Empirical Probability Distribution},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {11},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Zhou Yanru and Yang Jing},
  doi       = {10.14569/IJACSA.2023.0141199},
  url       = {https://doi.org/10.14569/IJACSA.2023.0141199}
}