Chongfu Huang

It has been observed that, before some strong earthquakes occur, the space static electricity near the ground is abnormal, which might be caused by a large amount of radioactive gas released from the Earth's crust. In this paper, the information diffusion technology for optimally processing small samples is used to analyze 30 cases, and the relationship between magnitude and parameters such as abnormality of space static electricity is constructed. Each case is composed of four observation values: abnormality e, epicenter distance d, impending time t and magnitude m. Using the causal relationship constructed in this paper, the magnitude m of an impending earthquake could be approximately inferred from abnormality e. According to the progress of locking the epicenter and the passage of time, the predicted magnitude could be adjusted in a timely manner. The research results provided in this paper do not eliminate the uncertainty of earthquake occurrence, so that the study is a work of analyzing seismic dynamic risk.Integrating the monitoring information from seismic stations and the physical field information in the air will promote impending earthquake prediction, which is a worldwide scientific challenge.

This paper reviews the main contents of the following picture book: Guide for travelling in an uncertain world: what is risk? Zhang, J., and Huang, H.W. 2022. Shanghai: Tongji University Press (ISBN: 978-7-5765-0351-7) (in Chinese). This picture book can help children and their parents become aware of risk, learn the knowledge about risk analysis, and cultivate interests related to the science, technology, engineering, and mathematics behind risk analysis. It is a welcome and successful contribution to the education of risk analysis to the child and the public.

It is easy to write a story about the Coronavirus Disease 2019 (COVID-19) when everything about COVID-19 is known. It is difficult to analyze the death risks of COVID-19 with a few evidences collected before and at the beginning of the outbreak. In this paper, we suggest a hybrid model to analyze the death risk under incomplete information. The hybrid model would be supported by the internet of intelligences, being a platform interacting with infectious disease specialists and local doctors who fuse the evidences with the experience of the known infectious diseases and provide a series of judgments related to the death risk of a human population in a given period to COVID-19. The hybrid model consists of two models of set-valued statistics and a formula. The set-valued statistics integrate the judgments for constructing (1) a probability distribution of the percent of patients, as the exposure of the population, and (2) a mortality curve with respect to the percent, as the vulnerability of the population. The suggested formula calculates the expected value of death toll. We give a virtual case to show how to use the hybrid model.

With the changes in the nature and the society, risks will inevitably change. It implies that, with the passage of time, some historical data would be invalid for probabilistic risk analysis. In this paper, a model to acquire the valid data is suggested, which is based on the Mann- Kendall test to detect abrupt change-point on time series data. What's more, the typhoon risk analysis in Guangdong Province, China is used as a case study to show how to apply the model. The valid data of the intensities of typhoons and the related losses in the province for the probabilistic risk analysis is obtained from the data during the time from 1984 to 2012. Comparing with the results based on the set of invalid data and the set of all collected data, the assessed risk based on the valid data is more reliable, which could reflect the dynamics of the typhoon risk.