基于关联规则——LSTM神经网络模型的“能源双碳数智”平台满意度分析
Satisfaction Analysis of “Energy Dual Carbon Digital Intelligence” Platform Based on Association Rule—LSTM Neural Network Model

“能源双碳数智”平台是能源新形势政策背景下，为政府机构、电网公司、企业、能源服务商等市场主要客户群体提供实现全方位碳监测与计量、多维度碳分析与评估、综合性碳资产管理、个性化碳账户与减排等服务的一体化智慧管控数字平台。该平台助力碳达峰、碳中和进程。在此背景下，本文首先基于ACSI模型建立平台满意度评价指标体系，借助关联规则——LSTM神经网络模型得出评价数据，对评价结果进行全面、详尽、客观的分析，为政府部门及企业提供客观、科学的数据分析资料，就如何推进“能源双碳数智”平台运行，提出一些具有推广价值的可行性经验。
Under the background of the new energy situation and policies, the “Energy Dual Carbon Digital In-telligence” platform provides government agencies, power grid companies, enterprises, energy service providers and other major customer groups in the market with an integrated intelligent management and control digital platform to achieve all-round carbon monitoring and measurement, multi-dimensional carbon analysis and assessment, comprehensive carbon asset management, personalized carbon account and emission reduction and other services. The platform facilitates the process of carbon peaking and carbon neutrality. In this context, this paper first establishes a platform satisfaction evaluation index system based on the ACSI model, obtains the evaluation data with the help of the association rule—LSTM neural network model, conducts a comprehensive, detailed and objective analysis of the evaluation results, provides objective and scientific data analysis data for government departments and enterprises, and puts forward some feasible experience with promotion value on how to promote the operation of the “energy dual carbon digital intelligence” platform.