Given its importance, fault diagnosis has attracted considerable attention in the literature, and several machine learning methods have been proposed to discover the characteristics of different aspects in fault diagnosis. In this paper, we propose a Hybrid Deep Belief Network (HDBN) learning model that integrates data in different ways for intelligent fault diagnosis in motor drive systems, such as a vehicle drive system. In particular, we propose three data fusion methods: data union, data join, and data hybrid, based on detailed data fusion research. Additionally, the significance of the fusion is explained from the energy perspective of the signal. In particular, the appropriate fusion methods and data structures suitable for model training requirements can help improve the accuracy of fault diagnosis. Moreover, mixed-precision training is used as a special fusion method to further improve the performance of the model. Experiments with the datasets obtained from the simulation platform demonstrate the superiority of our proposed model over the state-of-the-art methods.
Abstract. The network teaching system in higher education is playing an increasingly important role in modernization construction. Through the network teaching, creating a digital learning environment, to promote the reform of the education concept, teaching content and method, improve the teaching quality of education and improve students' ability of survival and development in the information society. The research content of this article to provide technical support for the teaching management system development. Based on the SQL Server database management system structure, conceptual structure design, logic structure design and the index design. In this paper, design of the database with reasonable structure, storage efficiency, as well as good independence, for the teaching management system development provides a feasible solution.
MOOC is the application of information technology in the field of education, changing the traditional teaching mode and providing students with a free and open learning environment. Based on the relevance learning theory, humanistic learning theory and educational psychology theory, this paper points out the advantages of MOOC in learning time, solving passive learning problems, learning resources more targeted, and strengthening interaction and communication. This paper analyzes the problems of fuzzy training objectives, less total class hours, and different computer foundations in computer basic course teaching. It also proposes to classify teaching resources, speed up teaching methods and means innovation, strengthen classroom interactive learning design, rationally transform teachers and students, and adopt a multi-evaluation system and other MOOC-based computer basic course teaching reform measures.
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