Research on the Global Wildlife Conservation Based on Analytic Hierarchy Process and Time Series Analysis Methods

This study addresses the issue of global illegal wildlife trade by proposing a Global Wildlife Conservation Program (GWCP) based on the Analytic Hierarchy Process (AHP) and time series analysis methods. The project aims to significantly reduce illegal trade, protect biodiversity, and promote ecological and economic sustainability through a fiveyear plan. Employing ARIMA and exponential smoothing techniques to forecast the project's effectiveness, and using least squares regression to evaluate the likelihood of project success, the study demonstrates a high probability of success at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{85.5\%}$</tex>, which remains robust at 75.7 % after sensitivity analysis. The research provides an effective strategy and tools for mitigating illegal wildlife trade worldwide.