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
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.
industrial parkrenewalsemi-digitalizationshock absorption and isolation
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