Incorporating knowledge of policy transfer into urban governance frameworks fosters cross-city learning and facilitates a transition from predictionbased to policy-guided decision-making.This approach combines data wi...Incorporating knowledge of policy transfer into urban governance frameworks fosters cross-city learning and facilitates a transition from predictionbased to policy-guided decision-making.This approach combines data with policy insights,expanding the scope of cross-city learning and fostering collaborative governance.Unlike traditional qualitative policy transfer studies,the envisioned policy-aware framework computationally translates policy contexts into quantitative representations for direct integration into machine learning,enabling automated strategy adaptation rather than relying solely on human interpretation.展开更多
基金funded by the NSFC(nos.72401174 and 52220105001)the Independent Research Project of the State Key Laboratory of Intelligent Green Vehicle and Mobility,Tsinghua University(no.ZZ-GG-20250403)Tsinghua University(State Key Laboratory of Intelligent Green Vehicle and Mobility)-Hangzhou Airport Economic Demonstration Zone Joint Research Center for Integrated Transportation.
文摘Incorporating knowledge of policy transfer into urban governance frameworks fosters cross-city learning and facilitates a transition from predictionbased to policy-guided decision-making.This approach combines data with policy insights,expanding the scope of cross-city learning and fostering collaborative governance.Unlike traditional qualitative policy transfer studies,the envisioned policy-aware framework computationally translates policy contexts into quantitative representations for direct integration into machine learning,enabling automated strategy adaptation rather than relying solely on human interpretation.
