With the aim of reducing the losses from water pollution, a dynamic risk assessment model for water quality is studied in this paper. This model is built on the projection pursuit cluster principle and risk indexes in the complex system, proceeding from the whole structure and its component parts. In this paper, the fuzzy analytic hierarchy process is used to screen out index system and determine index weight, while the further value of an index is simulated by hydrological model. The proposed model adopts the comprehensive dynamic evaluation method to analyze the time dimension data, and evaluates the development tendency by combining qualitative analysis with quantitative analysis. The projection pursuit theory is also employed for clustering the spatial dimension data, the optimal projection vector for calculating risk cluster type to compartmentalize risk, and then local conditions for proposing the regulation scheme. The applicational results show that the model has the strong logic superiority and regional adaptability with strict theoretical system, flexible methods, correct and reasonable results and simple implementation to provide a new way for research on risk assessment models of water quality.
A dynamic risk assessment model to assess the impact of coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
