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Lu Rui,Sheng Zhaohan
Strategic Study of CAE 2007, Volume 9, Issue 8, Pages 35-39
Keywords: technology learning innovation-self industry competence IC industry
Ethical Principles and Governance Technology Development of AI in China Review
Wenjun Wu, Tiejun Huang, Ke Gong
Engineering 2020, Volume 6, Issue 3, Pages 302-309 doi: 10.1016/j.eng.2019.12.015
Ethics and governance are vital to the healthy and sustainable development of artificial intelligence (AI). With the long-term goal of keeping AI beneficial to human society, governments, research organizations, and companies in China have published ethical guidelines and principles for AI, and have launched projects to develop AI governance technologies. This paper presents a survey of these efforts and highlights the preliminary outcomes in China. It also describes the major research challenges in AI governance research and discusses future research directions.
Keywords: AI ethical principles AI governance technology Machine learning Privacy Safety Fairness
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1677-1
● MSWNet was proposed to classify municipal solid waste.
Keywords: Municipal solid waste sorting Deep residual network Transfer learning Cyclic learning rate Visualization
Spatial prediction of soil contamination based on machine learning: a review
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1
● A review of machine learning (ML) for spatial prediction of soil
Keywords: Soil contamination Machine learning Prediction Spatial distribution
Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 11, doi: 10.1007/s11783-023-1738-5
● A novel integrated machine learning method to analyze O3
Keywords: Ozone Integrated method Machine learning
Machine learning in building energy management: A critical review and future directions
Frontiers of Engineering Management 2022, Volume 9, Issue 2, Pages 239-256 doi: 10.1007/s42524-021-0181-1
Keywords: building energy management machine learning integrated framework knowledge evolution
Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2, Pages 183-197 doi: 10.1007/s11705-021-2073-7
Keywords: machine learning flowsheet simulations constraints exploration
Learning from Academician Qian Xuesen
Song Jian
Strategic Study of CAE 2001, Volume 3, Issue 12, Pages 1-7
Keywords: Qian Xuesen Marxist philosophy science and technology engineering cybernetics systems science complex
Machine learning for fault diagnosis of high-speed train traction systems: A review
Frontiers of Engineering Management doi: 10.1007/s42524-023-0256-2
Keywords: high-speed train traction systems machine learning fault diagnosis
Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework
Frontiers of Structural and Civil Engineering Pages 994-1010 doi: 10.1007/s11709-023-0942-5
Keywords: dynamic prediction moving trajectory pipe jacking GRU deep learning
Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature
Frontiers of Medicine 2023, Volume 17, Issue 4, Pages 768-780 doi: 10.1007/s11684-023-0982-1
Keywords: machine learning methods hypertrophic cardiomyopathy genetic risk
Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7
Keywords: deep reinforcement learning hyper parameter optimization convolutional neural network fault diagnosis
Automated synthesis of steady-state continuous processes using reinforcement learning
Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2, Pages 288-302 doi: 10.1007/s11705-021-2055-9
Keywords: automated process synthesis flowsheet synthesis artificial intelligence machine learning reinforcementlearning
State-of-the-art applications of machine learning in the life cycle of solid waste management
Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 4, doi: 10.1007/s11783-023-1644-x
● State-of-the-art applications of machine learning (ML) in solid waste
Keywords: Machine learning (ML) Solid waste (SW) Bibliometrics SW management Energy utilization Life cycle
Communicative Learning: A Unified Learning Formalism Review
Luyao Yuan, Song-Chun Zhu
Engineering 2023, Volume 25, Issue 6, Pages 77-100 doi: 10.1016/j.eng.2022.10.017
Keywords: Artificial intelligencehine Cooperative communication Machine learning Pedagogy Theory of mind
Title Author Date Type Operation
Innovation self, Technology Learning and Elevation of Industry Competence — Case of Taiwan IC Industry
Lu Rui,Sheng Zhaohan
Journal Article
Ethical Principles and Governance Technology Development of AI in China
Wenjun Wu, Tiejun Huang, Ke Gong
Journal Article
MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal
Journal Article
Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method
Journal Article
Machine learning in building energy management: A critical review and future directions
Journal Article
Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet
Journal Article
Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework
Journal Article
Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature
Journal Article
A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis
Journal Article
Automated synthesis of steady-state continuous processes using reinforcement learning
Journal Article
State-of-the-art applications of machine learning in the life cycle of solid waste management
Journal Article