Complicated multi-source heterogeneous data assimilation method

Abstract

The invention provides a complicated multi-source heterogeneous data assimilation method. The complicated multi-source heterogeneous data assimilation method comprises the steps that first, decision data information is collected, and data type features of the decision data information is analyzed; second, descriptive languages in the data type features are expressed in the form of an intuitionistic fuzzy set, and the descriptive languages and real numbers in the data type features are converted into interval numbers respectively; and third, normalization processing is performed on the intervalnumbers. The complicated multi-source heterogeneous data assimilation method has the advantages that according to complicated multi-source heterogeneous data, digital expression of descriptive textsis realized, the uncertainty and fuzziness of description content are considered in the processing method, data structure features of the real numbers, intuitionistic fuzzy numbers and the interval numbers are analyzed and converted into the same data structure, normalization processing is performed, and measurement standards are unified.

Description

technical field [0001] The invention relates to a complex multi-source heterogeneous data assimilation method. Background technique [0002] When making a decision, mixed data information is often generated due to different decision-making goals or different representation forms of the decision-maker, resulting in incommensurability and contradictions among the indicators when making a decision. Decision-making based on multi-source heterogeneous indicators has been widely used in the fields of comprehensive evaluation, program optimization, effectiveness evaluation, and combat decision-making. Therefore, multi-source heterogeneous indicators need to be assimilated, so as to provide decision-making models with unified forms and measurement units. Indicator data. [0003] At present, most of the existing processing solutions for multi-source heterogeneous data are aimed at the problem that the same index has the same data structure, and the data structures of different index...

AI Technical Summary

Problems solved by technology

[0009] However, in the actual decision-making process, due to the complexity of the decision-making problem itself and the incompleteness of the data, the sources of decision-making indicators are rich, the types are diverse, and the measurement units are also different.

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