Abstract
We proposed a Hierarchical Fuzzy Inference System (HFIS) framework to offer better decision supports with fewer user-defined data (uncertainty). The framework consists two parts: a fuzzified Geographic Information System (GIS) and a HFIS system. The former provides comprehensive information on the criterion unit and the latter helps in making more robust decisions. The HFIS and the traditional Multi-Criteria Decision Making (MCDM) method were applied to a case study and compared. The fuzzified GIS maps maintained a majority of the dominant characteristics of the criterion unit but also revealed some non-significant information according to the surrounding environment. The urban planning map generated by the two methods shares similar strategy choices (6% difference), while the spatial distribution of strategies shares 69.7% in common. The HFIS required fewer subjective decisions than the MCDM (34 user-defined decision rules vs. 141 manual evaluations).
Highlights
With the tremendous development in China over the past few decades, various problems resulting from rapid urbanization, population growth, and climate change have emerged
We developed an applicable decision-making framework that applies a hierarchical fuzzy inference system (FIS) system [24] on a fuzzified Geographic Information System (GIS) system, in order to offer better decision supports with fewer user-defined data
In regard to the spatial distribution of the strategies, 69.7% of the resort planning generated by the Hierarchical Fuzzy Inference System (HFIS) uses the exact same strategy as that used by Multi-Criteria Decision Making (MCDM)
Summary
With the tremendous development in China over the past few decades, various problems resulting from rapid urbanization, population growth, and climate change have emerged. The Sponge City concept was proposed in 2012 in China during the Low-Carbon Urban. Similar concepts in urban planning, such as Best Management Practices [2], Low Impact. Development [3], and Water Sensitive Urban Design [4] have been successfully practiced, but there is still a long way to go to adapt, improve, and develop proper techniques, strategies, and planning methods to meet local conditions and needs in China. Followed by a barrage of government-issued policies, several cities in China with different population densities, spatial scales, and climate conditions are currently sponsored to explore the applicative national strategy and practice of Sponge City by the 2020s. Current Sponge City designs and construction plans do not satisfy our expectations [1]. Powerful, and accurate models and tools to support decision making
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