Model Building for Regional Ecological Risk Prediction and Evaluation of Prediction Accuracy

Autor: Jia Shao, Bei-lan Li, Wei-jun Liu, Min Chen
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Advances in Civil Engineering, Vol 2021 (2021)
Druh dokumentu: article
ISSN: 1687-8086
1687-8094
DOI: 10.1155/2021/6209506
Popis: The regional ecological risk model is built to predict the regional ecological risk level more accurately by using principal component analysis and optimizing standard BP neural network. Taking Xiangxi Tujia and Miao Autonomous Prefecture as an example, twelve primary factors affecting regional risk are selected. The sample data are processed by principal component analysis. The obtained main components are then used as input factors of the improved BP neural network, and the level of ecological risk is used as output factor. The results indicate that the error between the expected output and the actual output is 4.36% in 2016, 1.08% in 2017, and 5.18% in 2018, respectively, with all controlled within 6%. Compared with the prediction accuracy made by standard BP neural network without principal component analysis, the prediction accuracy made by improved BP neural network with principal component analysis is greatly improved. This comprehensive prediction model provides a better evaluation method for prediction of ecological risk level.
Databáze: Directory of Open Access Journals
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