Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

References

• Altman, N. S. 1992. “An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression.” The American Statistician 46 (3): 175–185.
   Web of Science ®Google Scholar
• Alvaro, P. , T. Condie , N. Conway , K. Elmeleegy , J. M. Hellerstein , and R. Sears . 2010. “Boom Analytics: Exploring Data-Centric, Declarative Programming for the Cloud.” In Proceedings of the 5th European Conference on Computer Systems (EuroSys) . Paris
   Google Scholar
• Apache . 2014. “Hadoop MapReduce.” https://hadoop.apache.org/
   Google Scholar
• Azadeh, A. , M. Saberi , A. Kazem , V. Ebrahimipour , A. Nourmohammadzadeh , and Z. Saberi . 2013. “A Flexible Algorithm for Fault Diagnosis in A Centrifugal Pump with Corrupted Data and Noise Based on ANN and Support Vector Machine with Hyper-Parameters Optimization.” Applied Soft Computing 13 (3): 1478–1485. doi:10.1016/j.asoc.2012.06.020.
   Web of Science ®Google Scholar
• Azoidou, E. , Z. Pang , Y. Liu , D. Lan , G. Bag , and S. Gong . 2017. “Battery Lifetime Modeling and Validation of Wireless Building Automation Devices in Thread.” 14 (7): 2869–2880. IEEE Transactions on Industrial Informatics.
   Web of Science ®Google Scholar
• Baba, A. I. , L. Hua , T. B. Pedersen , and M. Jaeger . 2017. “Cleansing Indoor RFID Tracking Data.” SIGSPATIAL Special 9 (1): 11–18. doi:10.1145/3124104.3124108.
   Google Scholar
• Babar, M. , F. Arif , M. A. Jan , Z. Tan , and F. Khan . 2019. “Urban Data Management System: Towards Big Data Analytics for Internet of Things Based Smart Urban Environment Using Customized Hadoop.” Future Generation Computer Systems 96: 398–409. doi:10.1016/j.future.2019.02.035.
   Web of Science ®Google Scholar
• Bandyopadhyay, P. S. , and M. R. Forster . 2011. Philosophy of Statistics . North Holland: Elsevier.
   Google Scholar
• Battré, D. , S. Ewen , F. Hueske , O. Kao , V. Markl , and D. Warneke . 2010. “Nephele/PACTs: A Programming Model and Execution Framework for Web-Scale Analytical Processing (Socc).” In Proceedings of the 1st ACM Symposium on Cloud Computing . Indianapolis, IN.
   Google Scholar
• Beaver, D. , H. C. Sanjeev Kumar , J. S. Li , and P. Vajgel . 2010. “Finding a Needle in Haystack: Facebook’s Photo Storage.” In Proceedings of the 9th USENIX Conference on Operating Systems Design and Implementation (OSDI) .Vancouver, BC.
   Google Scholar
• Bhandari, S. , N. Bergmann , R. Jurdak , and B. Kusy . 2017. “Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature.” Sensors 17: 6. doi:10.3390/s17050968.
   Web of Science ®Google Scholar
• Bu, Y. , B. Howe , M. Balazinska , and M. D. Ernst . 2010. “HaLoop: Efficient Iterative Data Processing on Large Clusters.” Proceedings of the VLDB Endowment 3: 1–2. doi:10.14778/1920841.1920881.
   Google Scholar
• Casado, R. , and M. Younas . 2015. “Emerging Trends and Technologies in Big Data Processing.” Concurrency and Computation : Practice & Experience 27 (8): 2078–2091. doi:10.1002/cpe.3398.
   Web of Science ®Google Scholar
• Chaiken, R. , B. Jenkins , P.-Å. Ke Larson , B. Ramsey , D. Shakib , S. Weaver , and J. Zhou . 2008. “SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets.” Proceedings of the VLDB Endowment 1 (2): 1265–1276. doi:10.14778/1454159.1454166.
   Google Scholar
• Chi, Q. , H. Yan , C. Zhang , Z. Pang , and L. D. Xu . 2014. “A Reconfigurable Smart Sensor Interface for Industrial WSN in IoT Environment.” IEEE Transactions on Industrial Informatics 10 (2): 1417–1425. doi:10.1109/TII.2014.2306798.
   Web of Science ®Google Scholar
• Dean, J. , and S. Ghemawat . 2008. “MapReduce: Simplified Data Processing on Large Clusters.” Communications of the ACM 51 (1): 107–113. doi:10.1145/1327452.
   Web of Science ®Google Scholar
• Deng, C. , R. Guo , C. Liu , R. Y. Zhong , and X. Xun . 2018. “Data Cleansing for Energy-Saving: A Case of Cyber-Physical Machine Tools Health Monitoring System.” International Journal of Production Research 56 (1–2): 1000–1015. doi:10.1080/00207543.2017.1394596.
   Web of Science ®Google Scholar
• Drakaki, M. , and P. Tzionas . 2017. “Manufacturing Scheduling Using Colored Petri Nets and Reinforcement Learning.” Applied Sciences 7: 2. doi:10.3390/app7020136.
   Google Scholar
• Ekanayake, J. , L. Hui , B. Zhang , T. Gunarathne , S.-H. Bae , J. Qiu , and G. Fox . 2010. “Twister: A Runtime for Iterative MapReduce.” In Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (HPDC) . Chicago, IL.
   Google Scholar
• Elnikety, E. , T. Elsayed , and H. E. Ramadan . 2011. “iHadoop: Asynchronous Iterations for MapReduce.”
   Google Scholar
• Ertek, G. , X. Chi , and A. N. Zhang . 2017. “A Framework for Mining RFID Data from Schedule-Based Systems.” IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (11): 2967–2984. doi:10.1109/TSMC.2016.2557762.
   Web of Science ®Google Scholar
• Esposito, C. , A. Castiglione , B. Martini , and K. K. R. Choo . 2016. “Cloud Manufacturing: Security, Privacy, and Forensic Concerns.” IEEE Cloud Computing 3 (4): 16–22. doi:10.1109/MCC.2016.79.
   Web of Science ®Google Scholar
• Gerlach, I. , V. C. Hass , and C.-F. Mandenius . 2015. “Conceptual Design of an Operator Training Simulator for a Bio-Ethanol Plant.” Processes 3 (3): 664–683. doi:10.3390/pr3030664.
   Web of Science ®Google Scholar
• Ghemawat, S. , H. Gobioff , and S.-T. Leung . 2003. “The Google File System.” In Proceedings of ACM SOSP . Bolton Landing, NY.
   Google Scholar
• Guerra, J. , H. Pucha , J. Glider , W. Belluomini , and R. Rangaswami . 2011. “Cost Effective Storage Using Extent Based Dynamic Tiering.” In Proceedings of the 9th USENIX Conference on File and Stroage Technologies (FAST) . San Jose, CA.
   Google Scholar
• Han, J. , M. Kamber , and J. Pei . 2012. Data Mining: Concepts and Techniques . Third ed. Boston, USA: Morgan Kaufmann.
   Google Scholar
• Hennebert, C. , and J. D. Santos . 2014. “Security Protocols and Privacy Issues into 6lowpan Stack: A Synthesis.” IEEE Internet of Things Journal 1 (5): 384–398. doi:10.1109/JIOT.2014.2359538.
   Web of Science ®Google Scholar
• Hu, H. , Y. Wen , T. S. Chua , and X. Li . 2014. “Toward Scalable Systems for Big Data Analytics: A Technology Tutorial.” IEEE Access 2: 652–687. doi:10.1109/ACCESS.2014.2332453.
   Web of Science ®Google Scholar
• Hupfeld, F. , T. Cortes , B. Kolbeck , J. Stender , E. Focht , M. Hess , J. Malo , J. Marti , and E. Cesario . 2008. “The XtreemFS Architecture&Mdash;a Case for Object-Based File Systems in Grids.” Concurrency and Computation: Practice and Experience 20 (17): 2049–2060. doi:10.1002/cpe.1304.
   Web of Science ®Google Scholar
• Isard, M. , M. Budiu , Y. Yuan , A. Birrell , and D. Fetterly . 2007. “Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks.” SIGOPS Operating Systems Review 41 (3): 59–72. doi:10.1145/1272998.
   Google Scholar
• Jolliffe, I. T. 2002. Principal Component Analysis . New York, NY: Springer-Verlag.
   Google Scholar
• Kanungo, T. , D. M. Mount , N. S. Netanyahu , C. D. Piatko , R. Silverman , and A. Y. Wu . 2002. “An Efficient k-Means Clustering Algorithm: Analysis and Implementation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (7): 881–892. doi:10.1109/TPAMI.2002.1017616.
   Web of Science ®Google Scholar
• Kim, A. , O. Kyuhyup , J.-Y. Jung , and B. Kim . 2017. “Imbalanced Classification of Manufacturing Quality Conditions Using Cost-Sensitive Decision Tree Ensembles.” International Journal of Computer Integrated Manufacturing 31 (8): 701–717.
   Web of Science ®Google Scholar
• Kluczek, A. 2016. “Application of Multi-Criteria Approach for Sustainability Assessment of Manufacturing Processes.” Management and Production Engineering Review 7 (3): 62–78. doi:10.1515/mper-2016-0026.
   Web of Science ®Google Scholar
• Kusiak, A. 2017. “Smart Manufacturing Must Embrace Big Data.” Nature 544 (7648): 23. doi:10.1038/544161d.
   PubMed Web of Science ®Google Scholar
• Kusiak, A. 2018. “Smart Manufacturing.” International Journal of Production Research 56 (1–2): 508–517. doi:10.1080/00207543.2017.1351644.
   Web of Science ®Google Scholar
• Lade, P. , R. Ghosh , and S. Srinivasan . 2017. “Manufacturing Analytics and Industrial Internet of Things.” IEEE Intelligent Systems 32 (3): 74–79. doi:10.1109/MIS.2017.49.
   Web of Science ®Google Scholar
• Lei, Y. , F. Jia , J. Lin , S. Xing , and S. X. Ding . 2016. “An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data.” IEEE Transactions on Industrial Electronics 63 (5): 3137–3147. doi:10.1109/TIE.2016.2519325.
   Web of Science ®Google Scholar
• Leng, C. , L. Hao , S. Zhu , and R. Jin . 2018a. “Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM.” In AAAI . New Orleans, LA.
   Google Scholar
• Leng, K. , L. Jin , W. Shi , and I. Van Nieuwenhuyse . 2018b. “Research on Agricultural Products Supply Chain Inspection System Based on Internet of Things.” Cluster Computing . doi:10.1007/s10586-018-2021-6.
   Google Scholar
• Li, X. , J. Wan , H. Dai , M. Imran , M. Xia , and A. Celesti . 2019. “A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing.” IEEE Transactions on Industrial Informatics (Early Access) 1–9. https://ieeexplore.ieee.org/document/8643392
   Web of Science ®Google Scholar
• Li, X. , Q. Wang , H.-N. Dai , and H. Wang . 2018. “A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack.” Sensors 18 (6): 1–23.
   Web of Science ®Google Scholar
• Liao, Y. , H. Panetto , P. C. Stadzisz , and J. M. Simão . 2018. “A Notification-Oriented Solution for Data-Intensive Enterprise Information Systems A Cloud Manufacturing Case.” Enterprise Information Systems 12 (8–9): 942–959. doi:10.1080/17517575.2018.1470258.
   Web of Science ®Google Scholar
• Lin, Y. , S. Han , H. Mao , Y. Wang , and W. J. Dally . 2018. “Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training.” In International Conference on Learning Representations (ICLR) . Vancouver.
   Google Scholar
• Liu, H. , F. Eldarrat , H. Alqahtani , A. Reznik , X. de Foy , and Y. Zhang . 2017. “Mobile Edge Cloud System: Architectures, Challenges, and Approaches.” IEEE Systems Journal PP 99: 1–14.
   Google Scholar
• Low, Y. , D. Bickson , J. Gonzalez , C. Guestrin , A. Kyrola , and J. M. Hellerstein . 2012. “Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud.” Proceedings of the VLDB Endowment 5 (8): 716–727. doi:10.14778/2212351.2212354.
   Google Scholar
• Ma, H. , Y. Wang , and K. Wang . 2018. “Automatic Detection of False Positive RFID Readings Using Machine Learning Algorithms.” Expert Systems with Applications 91: 442–451. doi:10.1016/j.eswa.2017.09.021.
   Web of Science ®Google Scholar
• Malewicz, G. , M. H. Austern, A. J. C. Bik, J. C. Dehnert, I. Horn, N. Leiser, and G. Czajkowski. 2010. “Pregel: A System for Large-Scale Graph Processing.” In Proceedings of ACM SIGMOD .  Indianapolis, IN.
   Google Scholar
• Mekki, K. , E. Bajic , F. Chaxel , and F. Meyer . 2018. “A Comparative Study of LPWAN Technologies for Large-Scale IoT Deployment.” ICT Express .
   Google Scholar
• Molka-Danielsen, J. , P. Engelseth , and H. Wang . 2018. “Large Scale Integration of Wireless Sensor Network Technologies for Air Quality Monitoring at a Logistics Shipping Base.” Journal of Industrial Information Integration 10: 20–28. doi:10.1016/j.jii.2018.02.001.
   Web of Science ®Google Scholar
• Mourtzis, D. , E. Vlachou , N. Boli , L. Gravias , and C. Giannoulis . 2016. “Manufacturing Networks Design through Smart Decision Making Towards Frugal Innovation.” Procedia CIRP 50: 354–359. 26th CIRP Design Conference, Stockholm. http://www.sciencedirect.com/science/article/pii/S2212827116304061
   Google Scholar
• Newson, P. , and J. Krumm . 2009. “Hidden Markov Map Matching through Noise and Sparseness.” In Proceedings of ACM SIGSPATIAL . Seattle, WA.
   Google Scholar
• Petersen, S. , and S. Carlsen . 2011. “WirelessHART versus ISA100.11a: The Format War Hits the Factory Floor.” IEEE Industrial Electronics Magazine 5 (4): 23–34. doi:10.1109/MIE.2011.943023.
   Web of Science ®Google Scholar
• Post, F. H. , N. Gregory M , and G.-P. Bonneau . 2003. Data Visualization - the State of the Art . Springer-Verlag.
   Google Scholar
• Qiu, J. , W. Qihui , G. Ding , X. Yuhua , and S. Feng . 2016. “A Survey of Machine Learning for Big Data Processing.” EURASIP Journal on Advances in Signal Processing 2016 (1): 1–16.
   Google Scholar
• Ren, R. , T. Hung , and K. C. Tan . 2018. “A Generic Deep-Learning-Based Approach for Automated Surface Inspection.” IEEE Transactions on Cybernetics 48 (3): 929–940. doi:10.1109/TCYB.2017.2668395.
   PubMed Web of Science ®Google Scholar
• Russell, S. , and P. Norvig . 2009. Artificial Intelligence: A Modern Approach (3rd Edition) . 3rd ed. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Shvachko, K. , H. Kuang , S. Radia , and R. Chansler . 2010. “The Hadoop Distributed File System.” In Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST) , Washington, DC.
   Google Scholar
• Siddiqa, A. , I. A. Targio Hashem , I. Yaqoob , M. Marjani , S. Shamshirband , A. Gani , and F. Nasaruddin . 2016. “A Survey of Big Data Management: Taxonomy and State-Of-The-Art.” Journal of Network and Computer Applications 71: 151–166. doi:10.1016/j.jnca.2016.04.008.
   Web of Science ®Google Scholar
• Tao, F. , and Q. Qi . 2019. “New IT Driven Service-Oriented Smart Manufacturing: Framework and Characteristics.” IEEE Transactions on Systems, Man, and Cybernetics: Systems 49 (1): 81–91. doi:10.1109/TSMC.2017.2723764.
   Web of Science ®Google Scholar
• Tao, F. , Q. Qinglin , A. Liu , and A. Kusiak . 2018. “Data-Driven Smart Manufacturing.” Journal of Manufacturing Systems 48: 157–169. doi:10.1016/j.jmsy.2018.01.006.
   Web of Science ®Google Scholar
• Tasnim, S. , N. Pissinou , and S. S. Iyengar . 2017. “A Novel Cleaning Approach of Environmental Sensing Data Streams.” In 2017 14th IEEE Annual Consumer Communications Networking Conference (CCNC) , 632–633. Las Vegas.
   Google Scholar
• Telea, A. C. 2014. Data Visualization: Principles and Practice . Florida: CRC Press.
   Google Scholar
• Thusoo, A. , J. S. Sarma , N. Jain , Z. Shao , P. Chakka , N. Zhang , S. Antony , H. Liu , and R. Murthy . 2010. “Hive - a Petabyte Scale Data Warehouse Using Hadoop.” In IEEE 26th International Conference on Data Engineering (ICDE) . Long Beach, CA.
   Google Scholar
• Tran, T. X. , A. Hajisami , P. Pandey , and D. Pompili . 2017. “Collaborative Mobile Edge Computing in 5G Networks: New Paradigms, Scenarios, and Challenges.” IEEE Communications Magazine 55 (4): 54–61. doi:10.1109/MCOM.2017.1600863.
   Web of Science ®Google Scholar
• Trochim, W. M. K. , J. Donnelly , and K. Arora . 2016. Research Methods The Essential Knowledge Base . 2nd ed. Boston: Cengage Learning.
   Google Scholar
• Vapnik, V. N. 1995. The Nature of Statistical Learning Theory . New York, NY, USA: Springer-Verlag New York.
   Google Scholar
• Wang, H. , S. Fossen , F. Han , I. A. Hameed , and G. Li . 2016. “Towards Data-Driven Identification and Analysis of Propeller Ventilation.” In OCEANS , 1–6. Shanghai: IEEE.
   Google Scholar
• Wang, J. , M. Yulin , L. Zhang , R. X. Gao , and W. Dazhong . 2018a. “Deep Learning for Smart Manufacturing: Methods and Applications.” Journal of Manufacturing Systems 48: 144–156. doi:10.1016/j.jmsy.2018.01.003.
   Web of Science ®Google Scholar
• Wang, N. , X. Xiao , Y. Yang , T. D. Hoang , H. Shin , J. Shin , and Y. Ge 2018b. “PrivTrie: Effective Frequent Term Discovery under Local Differential Privacy.” In IEEE International Conference on Data Engineering (ICDE) .  Paris.
   Google Scholar
• Wang, P. , R. X. Gao , and Z. Fan . 2015. “Cloud Computing for Cloud Manufacturing: Benefits and Limitations.” Journal of Manufacturing Science and Engineering 137 (4): 1–9. doi:10.1115/1.4030209.
   Web of Science ®Google Scholar
• Wang, X. , W. Wang , L. T. Yang , S. Liao , D. Yin , and M. J. Deen . 2018a. “A Distributed HOSVD Method with Its Incremental Computation for Big Data in Cyber-Physical-Social Systems.” IEEE Transactions on Computational Social Systems 5 (2): 481–492. doi:10.1109/TCSS.2018.2813320.
   Web of Science ®Google Scholar
• Wang, X. , L. T. Yang , H. Liu , and M. J. Deen . 2018b. “A Big Data-as-A-Service Framework: State-of-the-Art and Perspectives.” IEEE Transactions on Big Data 4 (3): 325–340. doi:10.1109/TBDATA.2017.2757942.
   Web of Science ®Google Scholar
• Wang, X. , L. T. Yang , X. Xie , J. Jin , and M. J. Deen . 2017. “A Cloud-Edge Computing Framework for Cyber-Physical-Social Services.” IEEE Communications Magazine 55 (11): 80–85. doi:10.1109/MCOM.2017.1700360.
   Web of Science ®Google Scholar
• Wu, D. , C. Jennings , J. Terpenny , R. X. Gao , and S. Kumara . 2017a. “A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests.” Journal of Manufacturing Science and Engineering 139 (7): 071018. doi:10.1115/1.4036350.
   Web of Science ®Google Scholar
• Wu, D. , S. Liu , L. Zhang , R. X. Janis Terpenny , T. K. Gao , and J. A. Guzzo . 2017b. “A Fog Computing-Based Framework for Process Monitoring and Prognosis in Cyber-Manufacturing.” Journal of Manufacturing Systems 43: 25–34. doi:10.1016/j.jmsy.2017.02.011.
   Web of Science ®Google Scholar
• Wu, X. , V. Kumar , J. R. Quinlan , J. Ghosh , Q. Yang , H. Motoda , G. J. McLachlan et al. 2008. “Top 10 Algorithms in Data Mining.” Knowledge and Information Systems 14 (1): 1–37. DOI:10.1007/s10115-007-0114-2.
   Web of Science ®Google Scholar
• Wuest, T. , C. Irgens , and K.-D. Thoben . 2014. “An Approach to Monitoring Quality in Manufacturing Using Supervised Machine Learning on Product State Data.” Journal of Intelligent Manufacturing 25 (5): 1167–1180. doi:10.1007/s10845-013-0761-y.
   Web of Science ®Google Scholar
• Xu, J. , J. Yao , L. Wang , Z. Ming , K. Wu , and L. Chen . 2017. “Narrowband Internet of Things: Evolutions, Technologies and Open Issues.” IEEE Internet of Things Journal PP 99: 1–13.
   Google Scholar
• Zaharia, M. , M. Chowdhury , M. J. Franklin , S. Shenker , and I. Stoica . 2010. “Spark: Cluster Computing with Working Sets.” In Proceedings of the 2Nd USENIX Conference on Hot Topics in Cloud Computing (HotCloud) . Berkeley, CA.
   Google Scholar
• Zhang, G. P. 2000. “Neural Networks for Classification: A Survey.” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 30 (4): 451–462. doi:10.1109/5326.897072.
   Web of Science ®Google Scholar
• Zhang, Y. , Q. Gao , L. Gao , and C. Wang . 2012. “iMapReduce: A Distributed Computing Framework for Iterative Computation.” Journal of Grid Computing 10 (1): 47–68. doi:10.1007/s10723-012-9204-9.
   Web of Science ®Google Scholar
• Zhang, Y. , G. Zhang , J. Wang , S. Sun , S. Shubin , and T. Yang . 2015. “Real-Time Information Capturing and Integration Framework of the Internet of Manufacturing Things.” International Journal of Computer Integrated Manufacturing 28 (8): 811–822. doi:10.1080/0951192X.2014.900874.
   Web of Science ®Google Scholar
• Zheng, Z. , Y. Yang , X. Niu , H. N. Dai , and Y. Zhou . 2018. “Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids.” IEEE Transactions on Industrial Informatics 14 (4): 1606–1615. doi:10.1109/TII.2017.2785963.
   Web of Science ®Google Scholar
• Zhong, R. Y. , X. Chen , C. Chen , and G. Q. Huang . 2017. “Big Data Analytics for Physical Internet-Based Intelligent Manufacturing Shop Floors.” International Journal of Production Research 55 (9): 2610–2621. doi:10.1080/00207543.2015.1086037.
   Web of Science ®Google Scholar
• Zhong, R. Y. , G. Q. Huang , S. Lan , Q. Y. Dai , X. Chen , and T. Zhang . 2015. “A Big Data Approach for Logistics Trajectory Discovery from RFID-enabled Production Data.” International Journal of Production Economics 165: 260–272. doi:10.1016/j.ijpe.2015.02.014.
   Web of Science ®Google Scholar
• Zhong, R. Y. , S. Lan , X. Chen , Q. Dai , and G. Q. Huang . 2016. “Visualization of RFID-enabled Shopfloor Logistics Big Data in Cloud Manufacturing.” The International Journal of Advanced Manufacturing Technology 84 (1): 5–16. doi:10.1007/s00170-015-7702-1.
   Web of Science ®Google Scholar
• Zhou, Z.-H. 2012. Ensemble Methods: Foundations and Algorithms . 1st ed. Florida: Chapman & Hall/CRC.
   Google Scholar
• Zuo, Y. 2016. “Prediction of Consumer Purchase Behaviour Using Bayesian Network: An Operational Improvement and New Results Based on RFID Data.” International Journal of Knowledge Engineering and Soft Data Paradigms 5 (2): 85–105. doi:10.1504/IJKESDP.2016.075976.
   Google Scholar
• Zuo, Y. , F. Tao , and A. Y. C. Nee . 2018. “An Internet of Things and Cloud-Based Approach for Energy Consumption Evaluation and Analysis for a Product.” International Journal of Computer Integrated Manufacturing 31 (4–5): 337–348. doi:10.1080/0951192X.2017.1285429.
   Web of Science ®Google Scholar