Deep decision fusion method based on entropy evaluation method and D-S evidence theory

Abstract

The invention discloses a depth decision fusion method based on an entropy evaluation method and a D-S evidence theory, and belongs to the field of information fusion. Firstly, a plurality of classifiers are designed to carry out training recognition on samples, then single-layer decision fusion is carried out on recognition results of the multiple classifiers through an entropy evaluation method and a D-S evidence theory method; finally, a deep decision fusion method is adopted, and the result recognized by the method with the high recognition rate in the two decision fusion methods is reserved in each recognition process; and respective advantages of the two methods are fully exerted for identification. Compared with single classifier identification and single method decision fusion, the deep decision fusion method of the invention has higher identification accuracy, robustness and fault tolerance. Therefore, the method can be applied to various pattern recognition fields such as human body behavior recognition.

Description

technical field [0001] The invention relates to a deep decision-making fusion method based on an entropy value method and D-S evidence theory, belonging to the field of information fusion. Background technique [0002] With the development of artificial intelligence technology, pattern recognition has become an important research direction. As an important means of improving recognition accuracy and robustness in pattern recognition, information fusion plays an important role in the field of pattern recognition. It can integrate information from different sources, remove redundancy, and improve the robustness of the recognition system. and accuracy. Information fusion can be divided into three levels: data layer fusion, feature layer fusion, and decision-making layer fusion. The decision-making layer fusion combines the judgments of various sensors or classifiers to form the final reasoning and decision-making. It has strong flexibility and determines the accuracy of the d...

AI Technical Summary

Problems solved by technology

However, for systems that require high recognition accuracy, the single-layer decision fusion method cannot meet the requirements of the system.

Current research rarely uses deep decision fusion, that is, two or more decision fusion methods are used for decision fusion

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