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2. Activation functions selection for BP neural network model of ground surface roughness

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3. The architecture development of Industry 4.0 compliant smart machine tool system (SMTS)

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4. Wafer map defect pattern classification based on convolutional neural network features and error-correcting output codes

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   • Minghao Piao

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5. Swarm intelligence based centralized clustering: a novel solution

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6. Analysis of production cycle-time distribution with a big-data approach

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   • Lining Xing
   • Gaige Wang

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7. Unsupervised rotating machinery fault diagnosis method based on integrated SAE–DBN and a binary processor

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8. Towards an automated decision support system for the identification of additive manufacturing part candidates

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9. Nonlinear time-series modeling of feed drive system based on motion states classification

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   OriginalPaper 18 February 2020 Pages: 1935 - 1948

   

10. A research survey: heuristic approaches for solving multi objective flexible job shop problems

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11. Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology

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    • Rouqi Song

    OriginalPaper 22 February 2020 Pages: 1985 - 2002

    

12. Quality analysis in metal additive manufacturing with deep learning

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    • Xiaodong Jia
    • Jay Lee

    OriginalPaper 25 February 2020 Pages: 2003 - 2017

    

13. Various realization methods of machine-part classification based on deep learning

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    • Yan Shi
    • Weiqing Xu

    OriginalPaper 24 February 2020 Pages: 2019 - 2032

    

14. Two-sided matching decision-making model with hesitant fuzzy preference information for configuring cloud manufacturing tasks and resources

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    • Sheng Wang

    OriginalPaper 24 February 2020 Pages: 2033 - 2047

    

15. Design optimization by integrating limited simulation data and shape engineering knowledge with Bayesian optimization (BO-DK4DO)

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    • Mengying Zhou
    • Yan Yan

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16. Real-time task processing for spinning cyber-physical production systems based on edge computing

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17. Intelligent decision making for service and manufacturing industries

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