Biological species resources are the basis of human survival and the inexhaustible power of social and economic development, and are strategic resources for the sustainable development of the national economy. In order to solve the shortcomings of the existing research on wildlife nature conservation, based on the discussion of wildlife species resources, wildlife species resource values and artificial neural network models, this paper investigates and discusses the location, geological conditions, biomass data collection and artificial neural network parameter design of the study area. The wild biomass estimation model and threat prediction model based on artificial neural network are established. The experimental data show that the mean square error (MES) and nonlinear fitting rate (RNL) of the algorithm in biomass assessment and threat prediction of 20 sample sizes are 0.857 and 0.985 respectively. The algorithm has good performance.

Muhammad Safdar. Feasibility of Wildlife Conservation Based on Artificial Neural Network . Nature Environmental Protection (2020), Vol. 1, Issue 3: 28-36. https://doi.org/10.38007/NEP.2020.010304.

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