Research on the Knowledge Structure and Sustainable Development Pathways of Artificial Intelligence from the Perspective of Technological Science

Yuan Lin, Chenxi Xu, Kan Xu, Shiliang Zhang, Hui Liu () and Zhaoyun Zhang
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Yuan Lin: School of Public Administration and Policy, Dalian University of Technology, Dalian 116024, China
Chenxi Xu: School of Public Administration and Policy, Dalian University of Technology, Dalian 116024, China
Kan Xu: School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
Shiliang Zhang: School of Public Administration and Policy, Dalian University of Technology, Dalian 116024, China
Hui Liu: School of Foreign Languages, Dalian University of Technology, Dalian 116024, China
Zhaoyun Zhang: School of Public Administration and Policy, Dalian University of Technology, Dalian 116024, China

Sustainability, 2024, vol. 16, issue 20, 1-21

Abstract: Achieving significant breakthroughs in both the fundamental theories and technological applications of artificial intelligence is essential for fostering its long-term development. Under the guidance of Professor Qian Xuesen’s theory of technological science, exploring the internal mechanisms of knowledge evolution in artificial intelligence holds profound theoretical and practical significance for promoting sustainable technological advancement. This study draws on literature from the Web of Science (WOS) database and employs methods such as knowledge mapping, natural language processing, clustering analysis, and citation analysis to outline the knowledge structure of the field, clarify the trajectory of sustainable development, and trace the technological genealogy of VR/AR technologies.This study divides the knowledge structure within the field of technological science into “basic theoretical knowledge—applied basic knowledge—applied knowledge”, enriching Qian’s theory of technological science from within and providing strong intellectual support and technological pathways for sustainable technological development in practice. Artificial intelligence encompasses 10 distinct knowledge domains, among which machine learning and deep learning constitute the basic theoretical knowledge, data intelligence, computer vision, and swarm intelligence are the applied basic knowledge, and image processing and human-computer intelligence are the applied knowledge. The development of VR/AR technology has formed two main sustainable development paths: “machine learning—data intelligence—intelligent systems—human computer intelligence”, and “deep learning—computer vision—image processing”.

Keywords: artificial intelligence; technical science; knowledge graph; natural language processing; kmean++ (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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