Academic Journal of Computing & Information Science, 2025, 8(8); doi: 10.25236/AJCIS.2025.080805.
Huanjun Zu1, Zihang Zou2, Shuning He1
1School of Materials Science and Engineering, Hebei University of Technology, Tianjin, China, 300401
2School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin, China, 300401
The illicit wildlife trade represents a significant threat to global ecological balance, contributing to biodiversity loss and destabilizing ecosystems. In the United States, illegal wildlife trafficking has become a pressing concern, demanding the development and implementation of targeted countermeasures. To address this issue, this study proposes a novel framework incorporating advanced algorithms and a comprehensive risk assessment model tailored to the specific contextual factors of the United States. The model is constructed based on five key indicators: political stability, transportation infrastructure, level of digitalization, law enforcement capacity, and public awareness. To ensure the robustness of the index weight distribution, a dual-method approach integrating the Entropy Weight Method (EWM) and the Analytic Hierarchy Process (AHP) was employed. Analytical results indicate that the current risk level of illegal wildlife trade in the United States is 73.6%. To maintain adaptability to dynamic conditions, the study proposes a five-year strategic framework with annual reassessment mechanisms.
Illegal Wildlife Trade, Combat, EWM-AHP, MLA-BP Neural Network Algorithm
Huanjun Zu, Zihang Zou, Shuning He. Development of Strategic Frameworks for Combating Illegal Wildlife Trade. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 8: 27-34. https://doi.org/10.25236/AJCIS.2025.080805.
[1] Tomley F M, Shirley M W. Livestock infectious diseases and zoonoses[J]. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018, 2009 Vol. 364 No. 1530 (1530): pp. 2637-42.
[2] Brandis K J, Zawada K, Meagher P, et al. Development of tiliqua species provenance models for use in combating the illegal wildlife trade [J]. Frontiers in Ecology & Evolution, 2025. DOI:10.3389/fevo.2025.1526584.
[3] Fu Z, Wei J, Zhang Y, et al. Strategic study on reducing illegal wildlife trade based on system dynamics model[J].Proceedings of SPIE, 2024, 13219(000):9.DOI:10.1117/12.3035099.
[4] Sariyati N H, Ngadi E. Combating Illegal Trade of Monitor Lizards (Varanus spp) in Malaysia through DNA Barcoding Applications [J]. IOP Publishing Ltd, 2024.DOI:10.1088/1755-1315/1408/1/012008.
[5] Tlusty M F, Cassey P, Rhyne A L, et al.Species-level, digitized wildlife trade data are essential for achieving biodiversity targets[J].Proceedings of the National Academy of Sciences, 2024, 121(16):4. DOI:10.1073/pnas.2306869121.