Study on the assessment of illegal wildlife trade projects based on LSTM model and Monte Carlo simulation
DOI:
https://doi.org/10.54097/87pwpa59Keywords:
Illegal wildlife trade; LSTM modelling; Monte Carlo simulation; project evaluation.Abstract
The aim of this paper is to conduct an assessment study of illegal wildlife trade projects using LSTM models and Monte Carlo simulation techniques. Firstly, based on the data from 1994-2023, we predicted the number of illegal animal and plant trade in the next five years using LSTM model, and the results showed that although the number was on a decreasing trend, it was still high, indicating that the problem still needs to attract global attention. Subsequently, we used the Kendall correlation coefficient to analyse the relationship between the number of illegal trade counts and economic, environmental and climate indicators, and found a positive correlation with the economic losses from natural disasters and the number of extreme weather events. Finally, we identified seven key parameters affecting project success and simulated the posterior distributions of these parameters using the Markov Chain Monte Carlo method, and then conducted Monte Carlo simulations to estimate the probability of project success as 93.12%. Sensitivity analyses indicate that project success is most sensitive to the level of financial support and monitoring technology. Overall, using a data-driven approach, this paper provides an important reference for assessing illegal wildlife trade projects.
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