基于神经网络算法的城市生态环境设施智慧化建设类型识别及驱动机制
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国家自然科学基金面上项目(42271202)


Type identification and driving mechanism of intelligent construction of urban ecological environment facilities based on neural network algorithm
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    摘要:

    既有生态城市和智慧城市建设评价研究颇丰,但针对区域内城市生态环境设施智慧化建设类型分异及其复杂驱动机制的解析相对缺乏。以江苏省为研究范围,共划分53个研究单元,聚焦于与信通技术和数字基础设施相关的生态环境指标,从智慧生态环境监管平台、智慧生态环境信息传播平台、智慧生活、智慧生态环境创新潜力四个维度构建评价指标体系,采用加权TOPSIS对城市生态环境设施智慧化建设水平进行评价,并基于自组织映射神经网络划分建设类型,随后从人口规模、经济发展、基础设施、生态环境、居民生活与政府投入6个维度建立城市生态环境设施智慧化建设水平影响因素指标库,进而构建BP-DEMATEL-ISM复合多级递阶结构模型,探讨城市生态环境设施智慧化建设水平的直接和间接影响机制。研究发现:①江苏省城市生态环境设施智慧化建设水平表现出明显的市区>县级市>县现象;②建设类型可分为智慧发展引领型、智慧创新不足型、智慧生活特色型和智慧发展滞后型4类,且市区多为智慧发展引领型和智慧创新不足型,县级市和县多为智慧生活特色型和智慧发展滞后型;③城市生态环境设施智慧化整体建设水平的影响因素划分为4级,其中恩格尔系数和绿化覆盖率是最根本的深层影响指标,宽带用户数和人均电信业务量是最有效的直接影响指标;④分维度影响因素作用机制中人口规模、经济发展和居民生活三个维度的指标为城市生态环境设施智慧化建设水平的根本因素,是"经济基础决定上层建筑"哲学观的体现,三者直接作用并通过政府投入间接作用于基础设施和生态环境,进而影响最终的城市生态环境设施智慧化建设水平。研究可为提升城市生态环境设施智慧化建设水平提供科学参考。

    Abstract:

    There is a wealth of researches on the evaluation of eco-city and smart city construction, but there is a relative lack of analysis on the type identification and complex driving mechanisms of the urban eco-environment facilities intelligent construction. This paper takes Jiangsu province as the research area, with a total of 53 research units. Focusing on the eco-environment indicators related to ICT and digital infrastructure, an evaluation index system is constructed including supervision platform, information dissemination platform, smart life, and innovation potential. The paper evaluates the level of urban eco-environment facilities intelligent construction with weighted TOPSIS, and identifies construction types based on self-organizing mapping neural network. Then, the influencing factors system of urban eco-environment facilities intelligent construction is established from six dimensions: population size, economic development, infrastructure, ecological environment, residents' life, and government investment. The paper adopts BP-DEMATEL-ISM to explore the direct and indirect influencing mechanism of urban eco-environment facilities intelligent construction. The results show that: ① The overall ranking of urban eco-environment facilities intelligent construction is urban districts > county-level cities > counties; ② The construction types are divided into four categories including the intelligent leading development, intelligent innovation insufficiency, smart life featured, and the intelligent lagging development, and most of the urban districts are intelligent development leading type and intelligent innovation insufficient type, while most of the county-level cities and counties are smart life featured type and intelligent development lagging type; ③ The influencing factors of urban eco-environment facilities intelligent construction are divided into four levels, of which Engel's coefficient and green coverage rate are the most fundamental deep-seated influencing factors, while the number of Internet broadband access users and per capita telecommunication service volume are the most effective direct influencing factors; ④ From the perspective of sub-dimension, influencing factors of population size, economic development, and residents' life are fundamental, which is the embodiment of the philosophical view that "the economic foundation determines the superstructure". Factors of these three dimensions not only directly affect the urban eco-environment facilities intelligent construction, but also indirectly play a role by affecting the infrastructure and eco-environment through government investment. This paper can provide scientific reference for improving the level of urban eco-environment facilities intelligent construction.

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赵慧敏,胡宏,李可昕.基于神经网络算法的城市生态环境设施智慧化建设类型识别及驱动机制.生态学报,2024,44(11):4527~4543

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