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Computational Ecology and Software, 2023, 13(2): 43-51
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Article

A comprehensive risk assessment system for probabilistic problems

WenJun Zhang1, YanHong Qi2, Xin Li3
1School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
2Sun Yat-sen University Libraries, Sun Yat-sen University, Guangzhou 510275, China
3College of Plant Protection, Northwest A & F University, Yangling 712100, Shaanxi, China

Received 3 December 2022;Accepted 18 February 2023;Published online 20 April 2023;Published 1 June 2023
IAEES

Abstract
In present study we provided a comprehensive risk assessment system. The system consists of four representative methods, namely probability-deterministic assessment, probability-interval assessment, probability-ranking assessment, and probability-ranking with optimal mix strategy. Among them, the probability-interval assessment was proposed by us. In the risk assessment, there are multiple available states, but only one of them can occur in nature. The occurrence probability of each state is the determined value and interval respectively for the first two methods; and for the latter two methods it is the probability difference of each pair of adjacent states. Known the benefit matrix, plans ranking can be derived from the first three methods according to the expected benefit; the fourth method can be used to obtain the optimal mix proportion of plans. The Matlab full code of the assessment system was given for further application and improvement.

Keywords risk assessment;plans ranking;probability;risk and benefit;optimal mix proportion;Matlab.


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