Reducing the illegal wildlife trade based on multiple linear regression model

Illegal wildlife trade has serious negative impacts on the ecological environment and species diversity, and it is of practical significance to propose projects to reduce it for the protection of the ecological environment. By analyzing the problem around illegal wildlife trade, we constructed and continuously monitored and evaluated the improvement model to present the factors, formulate solutions and predict results affecting the illegal wildlife trade. We use EWM to calculate the weighting coefficients of the three organizations in relation to power, resources and interest. Finally we choose the UNEP as our client. 5a sliding window algorithm and social awareness rate formula are developed by us for comprehensive data analysis, ultimately resulting in a strong adaptation of program content to client goals. So as to achieve the goal of reducing the illegal wildlife trade behaviors and protecting the ecological environment. The paper could effectively reduce illegal wildlife trade, enhance public awareness of animal protection, maintaining an accurate level of prediction when responding to unforeseen events.