Qiaogang Yin, Yanlong Li, Ye Zhang, Lifeng Wen, Lei She, Xinjian Sun
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Assessment of loss of life caused by dam failure based on fuzzy theory and hybrid random forest model
Dam failure may lead to significant casualties among downstream residents. Therefore, it is crucial to study a reliable method to quantitatively assess the loss of life (LOL) caused by dam failure for emergency response to dam failure incidents. Based on a statistical analysis of typical dam failure accidents in China and the research on the formation mechanism of LOL, the study quantified the factors influencing LOL using fuzzy theory and constructed a quantitative database for the LOL. Then, it proposed an innovative algorithm integrating the grey wolf optimization (GWO) algorithm and the random forest (RF) model. Finally, a data-driven assessment model for the LOL caused by dam failure was developed by combining the gray correlation analysis of the factors. The performance of the GWO-RF model was validated using a dataset of the LOL caused. The proposed model was used to assess the LOL in typical dam failure events. The results indicate that the model has higher accuracy, with an average absolute error of approximately 945 persons, significantly lower than 2529 persons in the Graham method. Thus, it can effectively estimate the LOL caused by dam failure. This study developed a novel method for quantitatively assessing the LOL caused by dam failure, which could also serve as a reference for modeling disaster consequences in other fields.
期刊介绍：
Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas:
- Spatiotemporal analysis and mapping of natural processes.
- Enviroinformatics.
- Environmental risk assessment, reliability analysis and decision making.
- Surface and subsurface hydrology and hydraulics.
- Multiphase porous media domains and contaminant transport modelling.
- Hazardous waste site characterization.
- Stochastic turbulence and random hydrodynamic fields.
- Chaotic and fractal systems.
- Random waves and seafloor morphology.
- Stochastic atmospheric and climate processes.
- Air pollution and quality assessment research.
- Modern geostatistics.
- Mechanisms of pollutant formation, emission, exposure and absorption.
- Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection.
- Bioinformatics.
- Probabilistic methods in ecology and population biology.
- Epidemiological investigations.
- Models using stochastic differential equations stochastic or partial differential equations.
- Hazardous waste site characterization.
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