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Data analytics and optimization for smart industry

Lixin TANG, Ying MENG

Frontiers of Engineering Management 2021, Volume 8, Issue 2,   Pages 157-171 doi: 10.1007/s42524-020-0126-0

Abstract: First, this study describes a general methodology for the fusion of data analytics and optimization.Then, it identifies some data analytics and system optimization technologies to handle key issues inThe framework uses data analytics to perceive and analyze industrial production and logistics processesData analytics and system optimization technologies are employed in the four-level framework to overcomeThe fusion of data analytics and optimization allows enterprises to enhance the prediction and control

Keywords： data analytics     system optimization     smart industry    

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Intelligent data analytics is here to change engineering management

Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG

Frontiers of Engineering Management 2017, Volume 4, Issue 1,   Pages 41-48 doi: 10.15302/J-FEM-2017003

Abstract: Data enabling technology plays an important role in modern scientific discovery and technologic advancementThis position paper argues that data analytics is ready to change engineering management in the followingareas: 1) by making relevant historical data available to the manager at the time when it’s needed;2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful dataacquisition and data analytics.

Keywords： engineering management     project management     big data     data analytics     planning     execution    

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Special issue: Decision, risk analytics and data intelligence

Xiaozhe ZHAO, Desheng WU

Frontiers of Engineering Management 2020, Volume 7, Issue 2,   Pages 169-171 doi: 10.1007/s42524-020-0114-4

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CORRECTION to: Special issue: Decision, risk analytics and data intelligence

Xiaozhe ZHAO, Desheng Wu

Frontiers of Engineering Management   Pages 697-697 doi: 10.1007/s42524-020-0139-8

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The Industrial Internet Platform: Trend and Challenges

Wang Chen,Song Liang and Li Shaokun

Strategic Study of Chinese Academy of Engineering 2018, Volume 20, Issue 2,   Pages 15-19 doi: 10.15302/J-SSCAE-2018.02.003

Abstract: elaborated and the challenges in building the client-ecosphere, developer-ecosphere, as well as the data-ecosphereFurthermore, the technical challenges of IIP in modeling and analyzing industry big data system and industrydata are discussed in depth.

Keywords： industry Internet platform     industrial big data     data analytics    

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Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectivesin the Big Data Era Perspective

Chao Shang、 Fengqi You

Engineering 2019, Volume 5, Issue 6,   Pages 1010-1016 doi: 10.1016/j.eng.2019.01.019

Abstract: The burgeoning era of big data is influencing the process industries tremendously, providing unprecedentedTo attain this goal, data analytics and machine learning are indispensable.In this paper, we review recent advances in data analytics and machine learning applied to the monitoring

Keywords： Big data     Machine learning     Smart manufacturing     Process systems engineering    

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SuPoolVisor: a visual analytics system for mining pool surveillance Research

Jia-zhi XIA, Yu-hong ZHANG, Hui YE, Ying WANG, Guang JIANG, Ying ZHAO, Cong XIE, Xiao-yan KUI, Sheng-hui LIAO, Wei-ping WANG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 507-523 doi: 10.1631/FITEE.1900532

Abstract: is also a challenge to achieve intuitive and comprehensive monitoring of multi-source heterogeneous dataIn this study, we present SuPoolVisor, an interactive visual analytics system that supports surveillance

Keywords： Bitcoin mining pool     Visual analytics     Transaction data     Visual reasoning     FinTech    

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Special issue: Operations analytics and optimization for manufacturing, logistics and energy systems

Jiming WANG, Jie LIU, Anlin SHAO, Lixin TANG

Frontiers of Engineering Management 2017, Volume 4, Issue 3,   Pages 239-241 doi: 10.15302/J-FEM-2017109

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Cyber-Physical Production Systems for Data-Driven, Decentralized, and Secure Manufacturing—A Perspective Perspective

Manu Suvarna, Ken Shaun Yap, Wentao Yang, Jun Li, Yen Ting Ng, Xiaonan Wang

Engineering 2021, Volume 7, Issue 9,   Pages 1212-1223 doi: 10.1016/j.eng.2021.04.021

Abstract: holistic perspective on the role of the CPPS in three key and essential drivers of this transformation: data-drivenmanufacturing, decentralized manufacturing, and integrated blockchains for data security.to connect these three aspects of smart manufacturing and proposes that through the application of data-drivenLayering blockchain technologies on top of CPPS will ensure the reliability and security of data sharing

Keywords： Smart manufacturing     Cyber-physical production systems     Industrial Internet of Things     Data analytics    

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APFD: an effective approach to taxi route recommendation with mobile trajectory big data Research Article

Wenyong ZHANG, Dawen XIA, Guoyan CHANG, Yang HU, Yujia HUO, Fujian FENG, Yantao LI, Huaqing LI

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 10,   Pages 1494-1510 doi: 10.1631/FITEE.2100530

Abstract:

With the rapid development of data-driven intelligent transportation systems, an efficient methodeffective taxi approach (called APFD) based on the (APF) method and method with mobile trajectory big data

Keywords： Big data analytics     Region extraction     Artificial potential field     Dijkstra     Route recommendation     GPS    

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A Causal Model-Inspired Automatic Feature-Selection Method for Developing Data-Driven Soft Sensors in

Yan-Ning Sun,Wei Qin,Jin-Hua Hu,Hong-Wei Xu,Poly Z.H. Sun

Engineering 2023, Volume 22, Issue 3,   Pages 82-93 doi: 10.1016/j.eng.2022.06.019

Abstract: Many researchers have developed data-driven soft sensors using cutting-edge machine learning (ML) orfuture, this method can also be applied to other industrial processes to help develop more advanced data-driven

Keywords： Big data analytics     Machine intelligence     Quality prediction     Soft sensors     Intelligent manufacturing    

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Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Pai ZHENG, Honghui WANG, Zhiqian SANG, Ray Y. ZHONG, Yongkui LIU, Chao LIU, Khamdi MUBAROK, Shiqiang YU, Xun XU

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 137-150 doi: 10.1007/s11465-018-0499-5

Abstract: rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data

Keywords： Industry 4.0     smart manufacturing systems     Internet of Things     cyber-physical systems     big data analytics    

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RCAnalyzer: visual analytics of rare categories in dynamic networks Research

Jia-cheng PAN, Dong-ming HAN, Fang-zhou GUO, Da-wei ZHOU, Nan CAO, Jing-rui HE, Ming-liang XU, Wei CHEN

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 491-506 doi: 10.1631/FITEE.1900310

Abstract: structures and visualize them in the context to help oracles examine the analysis results and label the data

Keywords： Rare category detection     Dynamic network     Visual analytics    

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Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing discharge dispositions

Frontiers of Engineering Management   Pages 577-591 doi: 10.1007/s42524-022-0203-7

Abstract: Existing predictive analytics methods, such as distribution-/regression-based methods and machine learningIn this work, a data-driven predictive analytics approach is considered to jointly predict the individualizedA real case study using large-scale NH data is provided to demonstrate the superior prediction performanceThe developed analytics tools will allow NH management groups to identify the most at-risk residents

Keywords： nursing home     predictive analytics     individualized prediction     competing risks     health outcomes    

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A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

Frontiers of Engineering Management 2020, Volume 7, Issue 1,   Pages 27-46 doi: 10.1007/s42524-020-0092-6

Abstract: The era of big data brings unprecedented opportunities and challenges to management research.Exploring the applicable evaluation methods in the big data environment has become an important subjectpaper is to provide an overview and discussion of systematic evaluation and improvement in the big dataWe first review the evaluation methods based on the main analytic techniques of big data such as dataFocused on the characteristics of big data (association feature, data loss, data noise, and visualization

Keywords： big data     evaluation methods     systematic improvement     big data analytic techniques     data mining    

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Title Author Date Type Operation

Data analytics and optimization for smart industry

Lixin TANG, Ying MENG

Journal Article

Intelligent data analytics is here to change engineering management

Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG

Journal Article

Special issue: Decision, risk analytics and data intelligence

Xiaozhe ZHAO, Desheng WU

Journal Article

CORRECTION to: Special issue: Decision, risk analytics and data intelligence

Xiaozhe ZHAO, Desheng Wu

Journal Article

The Industrial Internet Platform: Trend and Challenges

Wang Chen,Song Liang and Li Shaokun

Journal Article

Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectivesin the Big Data Era

Chao Shang、 Fengqi You

Journal Article

SuPoolVisor: a visual analytics system for mining pool surveillance

Jia-zhi XIA, Yu-hong ZHANG, Hui YE, Ying WANG, Guang JIANG, Ying ZHAO, Cong XIE, Xiao-yan KUI, Sheng-hui LIAO, Wei-ping WANG

Journal Article

Special issue: Operations analytics and optimization for manufacturing, logistics and energy systems

Jiming WANG, Jie LIU, Anlin SHAO, Lixin TANG

Journal Article

Cyber-Physical Production Systems for Data-Driven, Decentralized, and Secure Manufacturing—A Perspective

Manu Suvarna, Ken Shaun Yap, Wentao Yang, Jun Li, Yen Ting Ng, Xiaonan Wang

Journal Article

APFD: an effective approach to taxi route recommendation with mobile trajectory big data

Wenyong ZHANG, Dawen XIA, Guoyan CHANG, Yang HU, Yujia HUO, Fujian FENG, Yantao LI, Huaqing LI

Journal Article

A Causal Model-Inspired Automatic Feature-Selection Method for Developing Data-Driven Soft Sensors in

Yan-Ning Sun,Wei Qin,Jin-Hua Hu,Hong-Wei Xu,Poly Z.H. Sun

Journal Article

Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Pai ZHENG, Honghui WANG, Zhiqian SANG, Ray Y. ZHONG, Yongkui LIU, Chao LIU, Khamdi MUBAROK, Shiqiang YU, Xun XU

Journal Article

RCAnalyzer: visual analytics of rare categories in dynamic networks

Jia-cheng PAN, Dong-ming HAN, Fang-zhou GUO, Da-wei ZHOU, Nan CAO, Jing-rui HE, Ming-liang XU, Wei CHEN

Journal Article

Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing discharge dispositions

Journal Article

A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

Journal Article