Cloud service platform design method based on multi-source heterogeneous big data fusion

Abstract

A cloud service platform design method based on multi-source heterogeneous big data fusion comprises the steps of multi-source heterogeneous big data integration framework construction oriented to industry application, multi-source heterogeneous big data fusion model and algorithm research based on a fuzzy D-S evidence theory, and cloud service platform development and application based on multi-source heterogeneous big data fusion. Multi-source heterogeneous big data can be processed in real time, the performance is improved, services are provided for related enterprises and institutions, and the effective utilization rate of the data is improved. The method is a cloud service platform based on multi-source heterogeneous big data fusion developed for industries of intelligent logistics, intelligent manufacturing, intelligent medical treatment and the like, automation, informatization and scientization of daily operation decisions of enterprises or institutions in related industries are promoted, and application demonstration is carried out at the same time.

Description

technical field [0001] The invention relates to the technical field of cloud service platform design, in particular to a cloud service platform design method based on multi-source heterogeneous big data fusion. Background technique [0002] With the continuous integration of the global economy and technology, the increasingly fierce competition in the market economy has put forward higher requirements for modern manufacturing and service industries. Higher requirements are put forward; and, with the rapid development of computer network technology, communication technology, signal detection and other technologies, people's requirements for the richness, accuracy, and real-time nature of data content have been and cannot be obtained by information from a single data source. Especially in the fields of modern intelligent manufacturing, intelligent logistics, and intelligent medical care, multi-source heterogeneous big data fusion technology is required. [0003] At present, d...

AI Technical Summary

Problems solved by technology

[0004] First, there are still difficulties in the real-time processing of multi-source heterogeneous big data; data files in logistics, manufacturing, medical and health industries have the characteristics of multi-source, heterogeneous, massive, dynamic, etc. Considering real-time requirements, design multi-source heterogeneous big data There are certain difficulties in the real-time data processing model;

[0005] Second, there is a problem of difficulty in obtaining the basic probability distribution function in D-S theory;

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