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Research on coupling coordination development based on neural network weight analysis

Published: 16 April 2024 Publication History

Abstract

In the process of human social development, the coupling and coordinated development between ecological environment (E), production (P), and living functions (L) are of great significance for sustainable development. (1) In this study, a more objective weight was obtained to minimize the analysis error caused by subjective judgment weights. In the quantitative analysis of the weights of various influencing factors, improved backpropagation neural networks (BPNN), grey model neural networks (GMNN), and generalized regression neural networks (GRNN) were developed to identify the nonlinear relationship between influencing factors and the "P-L-E space", Then, the Average Influence Algorithm (MIV) algorithm is used to calculate the weights of each influencing factor.(2) Using an improved coupling coordination analysis method, the coupling degree (DOC) values of E, P, and L were higher, but the coupling coordination degree (CCD) of the three was lower, especially the DOC values of E and L decreased the most.

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    ICMLCA '23: Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application
    October 2023
    1065 pages
    ISBN:9798400709449
    DOI:10.1145/3650215
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    Published: 16 April 2024

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