Affiliations: [a] Decision Sciences Institute, Fuzhou University, Fuzhou, China
| [b] Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
Abstract: Environmental governance cost prediction is an essential process in environmental protection. However, the existing environmental governance cost prediction methods are facing two challenges: First, the principal components of environmental indicator information must be accurately extracted without considering the independence of environmental indicators. Second, the higher interpretability and the lower complexity must be taken into account with the desired accuracy for improving the cost prediction of environmental governance. Therefore, the fuzzy rule based system (FRBS) and feature extraction are introduced to propose a new environmental governance cost prediction method, named FRBS-FE, in which the feature extraction is used to extract the principal components of environmental indicator information firstly, and then all these principal components are applied to generate a FRBS-FE for better environmental governance cost prediction. A case study involving 29 provinces of China is carried out to demonstrate the effectiveness of the FRBS-FE. The results showed that the FRBS-FE not only can accurately predict different kinds of environmental governance costs, but also have superior performance in comparison with previous cost prediction methods.
