Applying Back Propagation Algorithm and Analytic Hierarchy Process to Environment Assessment

TL;DR

This paper introduces a new environmental assessment method combining AHP and back propagation algorithms, demonstrating significant local and regional environmental improvements and validating the model's accuracy with high correlation.

Contribution

It develops a novel assessment model integrating AHP and back propagation algorithms for environmental quality evaluation, applied to Saihan dam and Beijing.

Findings

Local environmental quality improved by 7 times

Beijing's environmental quality improved by 13%

High correlation (99%) confirms model accuracy

Abstract

This paper designs a new and scientific environmental quality assessment method, and takes Saihan dam as an example to explore the environmental improvement degree to the local and Beijing areas. AHP method is used to assign values to each weight 7 primary indicators and 21 secondary indicators were used to establish an environmental quality assessment model. The conclusion shows that after the establishment of Saihan dam, the local environmental quality has been improved by 7 times, and the environmental quality in Beijing has been improved by 13%. Then the future environmental index is predicted. Finally the Spearson correlation coefficient is analyzed, and it is proved that correlation is 99% when the back-propagation algorithm is used to test and prove that the error is little.