Complex system risk inducement analysis method using FTA and GRA-coupled FAHP

Abstract

Provided is a complex system risk inducement analysis method using FTA and GRA-coupled FAHP. The method comprises establishing a complex system risk analysis model, a fuzzy judgment matrix, and a fuzzy consistent judgment matrix, ordering the fuzzy consistent judgment matrix, performing dimensionless treatment on data, solving a pole difference in a correlation coefficient, the correlation coefficient, and degree of correlation, establishing a complex system coupling correlation order model, ordering the calculated order relations of various inducements of the complex system and finding out a main factor resulting in a system risk. The model takes account of the real fault data of the complex system and expert experience. The FAHP determines the weights of various inducements, overcomes result distortion due to judgment with few data samples in the GRA method. The GRA method overcomes the heavy subjectivity of the FAHP. The method analyzes and researches accident inducements subjectively, objectively, qualitatively, and quantitatively, and achieves an analysis result consistent with a reality.

Description

technical field [0001] The invention relates to the field of risk assessment of complex systems, in particular to a method for analyzing risk causes of complex systems coupled with FTA and FAHP with GRA. Background technique [0002] With the continuous expansion of the scale of complex systems and the increase of uncertainty in the system environment, scholars at home and abroad have conducted a lot of research on the risk incentives of complex systems. The main existing methods are fault tree analysis, probability evaluation, and analytic hierarchy process. , neural network method, gray theory method, etc. These methods still have some deficiencies: Fault Tree Analysis (FTA) is good for finding the cause of accident risk, but the calculation process is complicated; although the probability evaluation method has been initially applied, its theoretical basis is still insufficient, and its practicability needs to be improved; The key step is to give the judgment matrix by th...

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Problems solved by technology

These methods still have some deficiencies: Fault Tree Analysis (FTA) is good for finding the cause of accident risk, but the calculation process is complicated; although the probability evaluation method has been initially applied, its theoretical basis is still insufficient, and its practicability needs to be improved; The key step is to give the judgment matrix by the experts, and then calculate the sorting vector, so whether the judgment matrix given by the experts has a satisfactory consistency is a very important issue, and there are problems such as subjectivity in the determination of weight and membership degree; neural network When the learning samples of the method are insufficient, the accuracy cannot be guaranteed, and when the sample size is too large, it will affect its generalization; the gray theory method is not accurate enough due to the use of different samples, and the use process is more complicated

[0004] At present, there is no relevant literature report on the analysis method of FTA, FAHP coupled with GRA

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