强化学习在动态环境园区改造决策中的应用分析——以北京某重型电机厂141单体检测鉴定为例  

Application of reinforcement learning in dynamic environment park renovation decision-making--A case study of the inspection and identification of 141 units in a heavy machinery factory in Beijing

作　　者：董道武 DONG Daowu(China Power Investment Engineering Research,Inspection and Evaluation Center Co.,Ltd.,Beijing 100097,China)

机构地区：[1]中电投工程研究检测评定中心有限公司,北京100097

出　　处：《中国高新科技》2024年第6期24-26,共3页

摘　　要：文章以北京某重型电机厂的改造项目为例,探讨了强化学习在老旧工业园区更新中的应用。研究显示,自主开发的Ntgale Ad系统通过半数字化手段提高了改造决策的效率。同时,减震隔震技术满足了园区特殊需求,如教育和医疗领域的长期规划。这项研究展示了强化学习在动态环境下的实用性,为城市工业园区的更新提供了新视角。This paper discusses the application of reinforcement learning in the renovation of old industrial parks,taking the renovation project of a heavy machinery factory in Beijing as an example.The study demonstrates that the independently developed Ntgale Ad system enhances decision-making efficiency in park renovations through semi-digitization.Additionally,the application of seismic isolation technology meets specific needs of the park,such as long-term planning in education and healthcare sectors.This research highlights the practicality of reinforcement learning in dynamic environments and offers a new perspective on the renewal of urban industrial parks.

关 键 词：工业园区 更新 半数字化 减震隔震 

分 类 号：TU984[建筑科学—城市规划与设计]