Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

November 11, 2023


Pages


DOI

Article

Research on the Construction Path of Vocational Education Virtual Simulation Training Base Combining Multi-source Data

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Authors

Yongzhi Hao Affiliation:
Marine Navigation School, Zhejiang International Maritime College, Zhoushan, Zhejiang, 315021, China.
and Shuangdong Liu Affiliation:
Marine Navigation School, Zhejiang International Maritime College, Zhoushan, Zhejiang, 315021, China.


Abstract

This research firstly analyzes the significance of the construction of a virtual simulation training base for vocational education and takes modern shipping as an example to explore the path of the construction of training. Secondly, through point cloud data processing, combined with the improved SAC-IA algorithm for multi-source data fusion processing, three-dimensional modeling of the training base can be achieved. Finally, a virtual simulation training platform for vocational education is designed by combining the key technologies and equipment for platform development, and the accuracy of 3D modeling with multi-source data fusion and the application of the platform are analyzed. The consequence shows that the significance of learning interest P=0.03<0.05, the significance of technical support P=0.01<0.05, and the significance of learning situation P=0.00<0.05. The virtual simulation training platform for vocational education, based on this study, can improve the learning satisfaction of higher vocational students.


Keywords

Point cloud data processing, Multi-source data fusion, SAC-IA algorithm, Virtual simulation, Practical training platform, 97D60


Citation

Hao, Y. & Liu, S. (2023). Research on the construction path of vocational education virtual simulation training base combining multi-source data. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01096

Published by: Engineering Journals

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