A Carbon Emission Evaluation Method Based on Reinforcement Learning and Urban Perception——Taking Dujiangyan as an Example
This article focuses on the research of carbon emission evaluation methods,with the city street view of Dujiangyan as the empirical basis.Considering that people's perception of urban carbon emissions mainly comes from the sky,buildings,vehicles,and regional locations,this study utilizes questionnaire surveys and urban perception to obtain partial data,and applies the method of reinforcement learning to construct a new model for urban carbon evaluation.Different from traditional research methods,this article proposes a weakly supervised learning method,combining deep reinforcement learning with the characteristics of Markov decision processes to simulate human-level perception abilities,and to comprehensively reflect subjectivity and objectivity.This approach provides a more accurate evaluation of residents'perception of carbon emissions,making the construction of CIM(Carbon Emission Evaluation Method),urban renewal,and urban management work more targeted,thereby improving people's satisfaction.
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