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Wang, J., Xu, C., Zhang, J., & Zhong, R. (2022). Big data analytics for intelligent manufacturing systems: A review. Journal of Manufacturing Systems, 62, 738-752.Search in Google Scholar
Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. X. (2017). A review on the practice of big data analysis in agriculture. Computers and electronics in agriculture, 143, 23-37.Search in Google Scholar
Ren, S., Zhang, Y., Liu, Y., Sakao, T., Huisingh, D., & Almeida, C. M. (2019). A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions. Journal of cleaner production, 210, 1343-1365.Search in Google Scholar
Hossain, E., Khan, I., Un-Noor, F., Sikander, S. S., & Sunny, M. S. H. (2019). Application of big data and machine learning in smart grid, and associated security concerns: A review. Ieee Access, 7, 13960-13988.Search in Google Scholar
Nguyen, T., Li, Z. H. O. U., Spiegler, V., Ieromonachou, P., & Lin, Y. (2018). Big data analytics in supply chain management: A state-of-the-art literature review. Computers & operations research, 98, 254-264.Search in Google Scholar
Qi, C. C. (2020). Big data management in the mining industry. International Journal of Minerals, Metallurgy and Materials, 27(2), 131-139.Search in Google Scholar
Zhou, L., Pan, S., Wang, J., & Vasilakos, A. V. (2017). Machine learning on big data: Opportunities and challenges. Neurocomputing, 237, 350-361.Search in Google Scholar
Khan, M., Wu, X., Xu, X., & Dou, W. (2017, May). Big data challenges and opportunities in the hype of Industry 4.0. In 2017 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.Search in Google Scholar
Habeeb, R. A. A., Nasaruddin, F., Gani, A., Hashem, I. A. T., Ahmed, E., & Imran, M. (2019). Real-time big data processing for anomaly detection: A survey. International Journal of Information Management, 45, 289-307.Search in Google Scholar
Deepa, N., Pham, Q. V., Nguyen, D. C., Bhattacharya, S., Prabadevi, B., Gadekallu, T. R., ... & Pathirana, P. N. (2022). A survey on blockchain for big data: Approaches, opportunities, and future directions. Future Generation Computer Systems, 131, 209-226.Search in Google Scholar
Grover, P., & Kar, A. K. (2017). Big data analytics: A review on theoretical contributions and tools used in literature. Global Journal of Flexible Systems Management, 18, 203-229.Search in Google Scholar
Cui, Y., Kara, S., & Chan, K. C. (2020). Manufacturing big data ecosystem: A systematic literature review. Robotics and computer-integrated Manufacturing, 62, 101861.Search in Google Scholar
Cheng, Y., Chen, K., Sun, H., Zhang, Y., & Tao, F. (2018). Data and knowledge mining with big data towards smart production. Journal of Industrial Information Integration, 9, 1-13.Search in Google Scholar
Sestino, A., Prete, M. I., Piper, L., & Guido, G. (2020). Internet of Things and Big Data as enablers for business digitalization strategies. Technovation, 98, 102173.Search in Google Scholar
Kaffash, S., Nguyen, A. T., & Zhu, J. (2021). Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis. International journal of production economics, 231, 107868.Search in Google Scholar
Shang, C., & You, F. (2019). Data analytics and machine learning for smart process manufacturing: Recent advances and perspectives in the big data era. Engineering, 5(6), 1010-1016.Search in Google Scholar
Mohammadpoor, M., & Torabi, F. (2020). Big Data analytics in oil and gas industry: An emerging trend. Petroleum, 6(4), 321-328.Search in Google Scholar
Hariri, R. H., Fredericks, E. M., & Bowers, K. M. (2019). Uncertainty in big data analytics: survey, opportunities, and challenges. Journal of Big data, 6(1), 1-16.Search in Google Scholar
Berisha, B., Mëziu, E., & Shabani, I. (2022). Big data analytics in Cloud computing: an overview. Journal of Cloud Computing, 11(1), 24.Search in Google Scholar
Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International journal of operations & production management, 37(1), 10-36.Search in Google Scholar
Lv, Z., Song, H., Basanta-Val, P., Steed, A., & Jo, M. (2017). Next-generation big data analytics: State of the art, challenges, and future research topics. IEEE Transactions on Industrial Informatics, 13(4), 1891-1899.Search in Google Scholar
Zhuang, Y. T., Wu, F., Chen, C., & Pan, Y. H. (2017). Challenges and opportunities: from big data to knowledge in AI 2.0. Frontiers of Information Technology & Electronic Engineering, 18, 3-14.Search in Google Scholar
Li, W. (2022). Big Data precision marketing approach under IoT cloud platform information mining. Computational intelligence and neuroscience, 2022(1), 4828108.Search in Google Scholar
Liu, H., Ong, Y. S., Shen, X., & Cai, J. (2020). When Gaussian process meets big data: A review of scalable GPs. IEEE transactions on neural networks and learning systems, 31(11), 4405-4423.Search in Google Scholar
Mohammadi, M., Al-Fuqaha, A., Sorour, S., & Guizani, M. (2018). Deep learning for IoT big data and streaming analytics: A survey. IEEE Communications Surveys & Tutorials, 20(4), 2923-2960.Search in Google Scholar
Sun, A. Y., & Scanlon, B. R. (2019). How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions. Environmental Research Letters, 14(7), 073001.Search in Google Scholar
Wang Xi, Hu Xinzhi, Fan Weibei & Wang Ruchuan.(2023).Efficient data persistence and data division for distributed computing in cloud data center networks.The Journal of Supercomputing(14),16300-16327.Search in Google Scholar
S. Vengadeswaran,S.R. Balasundaram & P. Dhavakumar.(2024).IDaPS — Improved data-locality aware data placement strategy based on Markov clustering to enhance MapReduce performance on Hadoop.Journal of King Saud University - Computer and Information Sciences(3),101973-.Search in Google Scholar
M. A. H. Wadud,M. A. Jafor,M. F. Mridha & M. M. Rahman.(2020).Similarity Measurement Technique for Measuring the Performance of Page Rank Algorithm Based on Hadoop.International Journal of Recent Technology and Engineering (IJRTE)(5),4712-4717.Search in Google Scholar
D. Rajeswari, V. Jawahar Senthilkumar, M. Prakash & S. Ramamoorthy.(2024).Modified MapReduce for efficient data management: a task scheduling technique.International Journal of Public Sector Performance Management(4),491-503.Search in Google Scholar
Sanati Shiva, Rouhani Modjtaba & Hodtani Ghosheh Abed.(2023).Information-theoretic analysis of Hierarchical Temporal Memory-Spatial Pooler algorithm with a new upper bound for the standard information bottleneck method..Frontiers in computational neuroscience1140782-1140782.Search in Google Scholar