Evaluation And Application of Low Carbon Neighborhoods Based on Large Language Model

Abstract

Against the backdrop of global warming, urbanization is accelerating and the number of urban residents is increasing day by day. As the main body of energy consumption and carbon emissions, the low-carbon transformation of cities has become an urgent issue that needs to be addressed. The planning, construction, and renewal of low-carbon neighborhoods, as the fundamental units of urban low-carbon development, are crucial for achieving the overall carbon neutrality goal. However, the current evaluation of low-carbon neighborhoods mainly relies on the subjective judgment of experts, lacking unified scientific quantitative standards and effective evaluation methods. The aim of this study is to introduce big data modeling methods into the evaluation research of urban low-carbon blocks, and construct a low-carbon block evaluation index system based on big language models. This system identifies five main evaluation dimensions, including spatial form, travel mode, efficiency, complete facilities, and green ecological environment, extracts specific evaluation content and standards for each dimension, and selects representative indicators for quantitative evaluation. The research methods include literature review, expert consultation, field investigation, Delphi method, analytic hierarchy process, etc., to ensure the scientific and accurate evaluation. The research results show that the constructed low-carbon block evaluation index system can effectively reflect the low-carbon construction level of the block. Through empirical research on S district, it was found that the low-carbon construction level in the area meets the standard, but there is still room for improvement. This study not only provides scientific basis for the evaluation of low-carbon neighborhoods, but also offers new ideas and methods for urban low-carbon development. Its importance and potential impact lie in promoting the low-carbon transformation of cities, facilitating the transformation and upgrading of the construction industry, improving the environmental quality of urban neighborhoods, and contributing to addressing global climate change.