Research Article
Suitability Evaluation and Analysis of the Human Settlement-Environment-Energy Coupling System Based on Information Entropy and Artificial Intelligence Algorithms
Wenjie Qi,
Xiaohua Yang*
,
Weiqi Xiang
Issue:
Volume 11, Issue 3, June 2026
Pages:
47-54
Received:
27 April 2026
Accepted:
4 June 2026
Published:
9 June 2026
Abstract: To address the issues of insufficient granularity and ambiguous identification of key driving factors in the evaluation of the Human Settlement-Environment-Energy (HSEE) coupling system, this study takes 30 Chinese provinces as research objects and constructs an interpretable coupling evaluation model based on "information entropy + artificial intelligence" using panel data from 2003 to 2023. Using classic AI algorithms (BP neural network, PCA, and SVM) combined with the entropy weight method, the model was constructed. The entropy weight method and PCA respectively calculated the system suitability scores, and the robustness was validated by the Spearman correlation test (r = 0.9392). Indicator importance was identified via BP neural network, SVM, and the Garson algorithm, and comprehensive weights were determined using the rank average method. The results show that: during the study period, the national average system suitability continuously increased with an average annual growth rate of 3.8%; eastern coastal provinces significantly outperformed western and northeastern regions; per capita water resources, per capita local fiscal revenue, and residential consumption level are the core driving factors; infrastructure indicators exhibit diminishing marginal returns; energy consumption and environmental protection indicators show nonlinear differentiation characteristics. This study integrates objective weighting and machine learning interpretability to provide a standardized methodological framework for evaluating the HSEE coupling system, offering data support for regional human settlement quality improvement and sustainable development policy making.
Abstract: To address the issues of insufficient granularity and ambiguous identification of key driving factors in the evaluation of the Human Settlement-Environment-Energy (HSEE) coupling system, this study takes 30 Chinese provinces as research objects and constructs an interpretable coupling evaluation model based on "information entropy + artificial inte...
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Research Article
Risk Assessment of LNG Supply Stations Based on Cloud Model
Dongdong Wang*,
Ying Chen,
Tong Wei
Issue:
Volume 11, Issue 3, June 2026
Pages:
55-64
Received:
23 March 2026
Accepted:
8 June 2026
Published:
11 July 2026
DOI:
10.11648/j.ijees.20261103.12
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Abstract: In the context of the energy transition towards "carbon peak" and "carbon neutrality" as well as the shift from coal to natural gas, the liquefied natural gas (LNG) industry has experienced rapid development. Nevertheless, frequent LNG accidents pose a serious threat to people's lives and property safety. Based on the statistical analysis of the data of gas accidents that occurred in China from 2017 to 2023, with the aim of exploring the safety risk factors of LNG supply stations, a comprehensive evaluation system for the safety level of liquefied natural gas supply station was established, encompassing four dimensions: human factor, equipment and facilities, environment, and management. By integrating cloud model, improved analytic hierarchy process and entropy weight method, a comprehensive evaluation method for the safety level of LNG gas supply station was proposed. Finally, the method was applied to the H LNG Supply Station in Beijing, the results show that the cloud characteristic values of the risk assessment level of H gas supply station were (7.33, 0.79, 0.22) and the risk assessment results were close to the medium level. The research results verify the effectiveness of the evaluation method, which can provide a theoretical basis for the safety management and scientific evaluation of LNG supply stations.
Abstract: In the context of the energy transition towards "carbon peak" and "carbon neutrality" as well as the shift from coal to natural gas, the liquefied natural gas (LNG) industry has experienced rapid development. Nevertheless, frequent LNG accidents pose a serious threat to people's lives and property safety. Based on the statistical analysis of the da...
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