Geo-Environmental Carrying Capacity Assessment and Analysis Based on BP Neural Network

Carrying capacity in ecology means the maximum number of a species that a given living environment can support. With the development of modern society and the emergence of environmental problems, the concept of carrying capacity has been introduced into anthropology and has changed greatly in connotation and form, and its concept has been extended and applied to the study of various aspects of the whole natural world. This work takes a certain district as the research area, and establishes the evaluation index system of regional geoenvironmental carrying capacity according to the relevant geological regulations and requirements. On the basis of obtaining the relevant index data, the experimental sample data are processed and evaluated through the fusion of entropy value weighting and the comprehensive index method, and the evaluation level of each sample data is determined through the analysis of the relevant geo-environment; the learning prediction ability of the BP neural network model is then synthesized, and the evaluation level of each sample data is determined through the analysis of the relevant geological environment. Then we integrated the learning and prediction ability of the BP neural network model to predict the carrying capacity of the geological environment of each sample, and divided the samples into two parts, (1) one part of the samples was trained in the BP neural network model through learning so that the model could get the prediction ability with the error close to the smallest, (2) the other part of the samples was used to test the good prediction efficacy of the BP model completed by the learning and training to prove the validity of the algorithms proposed by the present work. This proves the effectiveness of the algorithm proposed in this work.