Evidence fusion method based on improved evidence dissimilarity degree

Abstract

The invention provides an improved evidence dissimilarity index and an improved evidence fusion algorithm. The improved evidence dissimilarity index and the improved evidence fusion algorithm comprisethe following steps 1-6. The method comprises the following steps: step 1, calculating dissimilarity indexes among different evidence bodies based on proposed improved evidence dissimilarity; step 2,calculating the support degree between different evidence bodies according to the evidence dissimilarity degree, and constructing a support degree matrix; step 3, calculating a characteristic value and a characteristic vector of the support degree matrix; step 4, taking the feature vector corresponding to the maximum feature value as a weight coefficient of each evidence body; step 5, except forthe evidence with the maximum weight, correcting the rest evidence bodies by taking the weight coefficient as a discount factor; and step 6, performing evidence fusion on the corrected evidence body through a D-S combination formula, and completing a final decision. According to the method, the conflict degree between different evidence bodies can be evaluated more effectively, and the accuracy and precision of evidence fusion are improved, so that the decision risk is reduced.

Description

technical field [0001] The invention relates to the field of information technology, in particular to an evidence fusion method based on improved evidence dissimilarity. Background technique [0002] Decision-making is one of the indispensable activities in social practice, and occupies an important position in all fields of human beings. In real life, things happen with randomness, people's cognition is incomplete, and natural language is inaccurate and fuzzy, which leads to various uncertainties before making decisions. In the prior art, methods for dealing with uncertainty mainly include Bayesian reasoning, random set theory, and Dempster-Shafer (D-S) evidence theory, etc. [0003] The D-S evidence theory has certain advantages over other methods. It was proposed by Dempster, then perfected and promoted by his student Shafer, and finally formed a theoretical system for dealing with uncertainty problems, which can be regarded as a generalized probability theory method. It...

AI Technical Summary

Problems solved by technology

[0005] Therefore, the traditional D-S evidence theory often obtains results that are contrary to common sense when dealing with conflicting evidence, which leads to misjudgments in decision-making, which is not conducive to the application requirements of actual situations.

The disadvantage of using the weighted average method to fuse the body of evidence is that the initial evidence source is completely discarded, and the weak information in the evidence source is lost. When other new evidence is added and a second judgment is required, a better result cannot be obtained. effect, and even lead to wrong decisions

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