Economic risk analysis method of flood control engineering system based on stochastic simulation of triangular fuzzy numbers

  • Authors:

  • Ju-Liang Jin;Qiu-Ying Fan;Ming Zhang;Yu-Liang Zhou

  • Affiliations:

  • Chengdu Institute of Plateau Meteorology, CMA, Chengdu, China and School of Civil Engineering, Hefei University of Technology, Hefei, China;School of Civil Engineering, Hefei University of Technology, Hefei, China;College of Hydrology and Water Resources, Hohai University, Nanjing, China;School of Civil Engineering, Hefei University of Technology, Hefei, China

  • Venue:
  • CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Economic risk analysis of flood control engineering system is very important in risk management of flood disaster. The triangular fuzzy numbers theory was used to describe and deal with randomicity and fuzziness of economic risk system of flood control engineering, and the shortage and imprecision of datum information. In order to deal with the difficulties of operations of triangular fuzzy numbers and their functions, Monte-Carlo method was used to simulate triangular fuzzy numbers, which can transform the operations of triangular fuzzy numbers and their functions into the conventional operations of real numbers, and then a new economic Risk Analysis Method for flood control engineering system based on Stochastic Simulation of Triangular Fuzzy Numbers, named RAM-SSTFN for short, was established. The applied results of RAM-SSTFN show that economic benefit series of flood control engineering system can be simulated using Monte-Carlo method, that RAM-SSTFN can consider more complex things and give more exact computation results than the simple analysis methods of economic risk analysis of flood control engineering system, and that the common simple analysis methods should be used carefully in economic risk analysis of important regional flood control engineering system because their computation precision is not high. RAM-SSTFN can be used to deal with less, imprecise, random and fuzzy information, so it can be widely applied to risk management of different uncertainties systems.