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A new experience mining approach for improving low carbon city development
Author(s) -
Wu Ya,
Shuai Chenyang,
Wu Liu,
Shen Liyin,
Yan Jianzhong,
Jiao Liudan,
Liao Shiju
Publication year - 2020
Publication title -
sustainable development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.115
H-Index - 64
eISSN - 1099-1719
pISSN - 0968-0802
DOI - 10.1002/sd.2046
Subject(s) - reuse , process (computing) , perspective (graphical) , computer science , sustainable development , urban planning , management science , engineering , artificial intelligence , civil engineering , waste management , law , political science , operating system
Abstract Developing low carbon city (LCC) has been widely appreciated as an important strategy for sustainable development. In line with this, an increasing number of cities globally have launched low carbon practices in recent years and gained various types of experience. However, it appears that existing studies do not present methods of how to use these valuable LCC experience in solving new problems. This study therefore introduces an experience mining approach to assist decision‐makers in reusing previous experience when tailoring LCC development strategies. The mining approach consists of three processes, namely, collecting historical cases which have been experiencing LCC, establishing LCC experience base, and mining similar experience cases. This study innovates the existing experience mining approach by introducing a two‐step mining process with considering the perspective of problem‐based urban characteristics (PBUCs) and the perspective of solution‐based urban characteristics (SBUCs). The application of the introduced mining approach has been demonstrated by a case study, where Shenyang's energy structure is adopted as the target problem. The new experience mining approach provides a valuable reference for decision‐makers to retrieve similar cases for improving LCC development with the consideration of city characteristics.