Research Article
Distributed Data Collaborative Fusion Method for Industry-University-Research Cooperation Innovation System Based on Machine Learning
@INPROCEEDINGS{10.1007/978-3-030-67871-5_23, author={Wen Li and Hai-li Xia and Wen-hao Guo}, title={Distributed Data Collaborative Fusion Method for Industry-University-Research Cooperation Innovation System Based on Machine Learning}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I}, proceedings_a={ADHIP}, year={2021}, month={2}, keywords={Machine learning Innovation system Distributed data Fusion method}, doi={10.1007/978-3-030-67871-5_23} }- Wen Li
Hai-li Xia
Wen-hao Guo
Year: 2021
Distributed Data Collaborative Fusion Method for Industry-University-Research Cooperation Innovation System Based on Machine Learning
ADHIP
Springer
DOI: 10.1007/978-3-030-67871-5_23
Abstract
Computer technology and the Internet industry are developing rapidly, and the amount of data is exploding, and people are entering the era of big data. Massive data contains a lot of knowledge value, and machine learning can extract useful key information from massive data. There are many shortcomings in traditional fusion methods, in order to better process the data in machine learning, a distributed data collaborative fusion method based on machine learning and industry-university research cooperation innovation system is proposed. The method is analyzed by research method theory and method function. The method function mainly realizes the temporal and spatial fusion of data through time synchronization, delay and misalignment of uncertain data processing, data association and weighted fusion. The simulation experiment is carried out according to the design and implementation steps of the method, and the feasibility and use value of the method are verified by experiments, and the performance of this method is superior.
