Bibliografía

nocite: ‘³²’

Adithiyaa, T., D. Chandramohan, and T. Sathish. “Optimal Prediction of Process Parameters by GWO-KNN in Stirring-Squeeze Casting of AA2219 Reinforced Metal Matrix Composites.” Materials Today: Proceedings 21 (2020): 1000–1007.

Al-Abassi, Abdulrahman, Hadis Karimipour, Hamed HaddadPajouh, Ali Dehghantanha, and Reza M. Parizi. “Industrial Big Data Analytics: Challenges and Opportunities.” Handbook of Big Data Privacy, 2020, 37–61.

Bezerra, Aguinaldo, Ivanovitch Silva, Luiz Affonso Guedes, Diego Silva, Gustavo Leitão, and Kaku Saito. “Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis.” Sensors 19, no. 12 (2019): 2772.

Borgi, Tawfik, Adel Hidri, Benjamin Neef, and Mohamed Saber Naceur. “Data Analytics for Predictive Maintenance of Industrial Robots.” In 2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 412–17. IEEE, 2017.

Chai, Zheng, and Chunhui Zhao. “Enhanced Random Forest with Concurrent Analysis of Static and Dynamic Nodes for Industrial Fault Classification.” IEEE Transactions on Industrial Informatics 16, no. 1 (2019): 54–66.

Chen, Xiao-long, Pei-hong Wang, Yong-sheng Hao, and Ming Zhao. “Evidential KNN-Based Condition Monitoring and Early Warning Method with Applications in Power Plant.” Neurocomputing 315 (2018): 18–32.

Chomboon, Kittipong, Pasapitch Chujai, Pongsakorn Teerarassamee, Kittisak Kerdprasop, and Nittaya Kerdprasop. “An Empirical Study of Distance Metrics for k-Nearest Neighbor Algorithm.” In Proceedings of the 3rd International Conference on Industrial Application Engineering, Vol. 2, 2015.

Dinh-Tuan, Hai, Felix Beierle, and Sandro Rodriguez Garzon. “Maia: A Microservices-Based Architecture for Industrial Data Analytics.” In 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS), 23–30. IEEE, 2019.

Estakhroueiyeh, Hossein Rezaei, and Esmat Rashedi. “Detecting Moldy Bread Using an E-Nose and the KNN Classifier.” In 2015 5th International Conference on Computer and Knowledge Engineering (ICCKE), 251–55. IEEE, 2015.

Geng, Daoqu, Chengyun Zhang, Chengjing Xia, Xue Xia, Qilin Liu, and Xinshuai Fu. “Big Data-Based Improved Data Acquisition and Storage System for Designing Industrial Data Platform.” IEEE Access 7 (2019): 44574–82.

Gholizadeh, Majid, Mehdi Jamei, Iman Ahmadianfar, and Rashid Pourrajab. “Prediction of Nanofluids Viscosity Using Random Forest (RF) Approach.” Chemometrics and Intelligent Laboratory Systems 201 (2020): 104010.

Hubauer, Thomas, Steffen Lamparter, Mikhail Roshchin, Nina Solomakhina, and Stuart Watson. “Analysis of Data Quality Issues in Real-World Industrial Data.” In Annual Conference of the PHM Society, Vol. 5, 2013.

Kabugo, James Clovis, Sirkka-Liisa Jämsä-Jounela, Robert Schiemann, and Christian Binder. “Industry 4.0 Based Process Data Analytics Platform: A Waste-to-Energy Plant Case Study.” International Journal of Electrical Power & Energy Systems 115 (2020): 105508.

Kumar, NC Santosh, S. Uma Maheswari, P. V. Pramila, Rashmita Khilar, and Ashok Kumar. “Colour Based Object Classification Using KNN Algorithm for Industrial Applications.” In 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS), 1110–15. IEEE, 2022.

Lee, Jay, Hossein Davari Ardakani, Shanhu Yang, and Behrad Bagheri. “Industrial Big Data Analytics and Cyber-Physical Systems for Future Maintenance & Service Innovation.” Procedia Cirp 38 (2015): 3–7.

Lee, Jay, Behrad Bagheri, and Hung-An Kao. “Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial Informatics.” In International Proceeding of Int Conference on Industrial Informatics (INDIN), 1–6. Citeseer, 2014.

Li, Wendong, Chi Zhang, Fugee Tsung, and Yajun Mei. “Nonparametric Monitoring of Multivariate Data via KNN Learning.” International Journal of Production Research 59, no. 20 (2021): 6311–26.

Lin, Jun, and Lan Liu. “Research on Security Detection and Data Analysis for Industrial Internet.” In 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C), 466–70. IEEE, 2019.

Liu, CH Bryan, Benjamin Paul Chamberlain, Duncan A. Little, and Ângelo Cardoso. “Generalising Random Forest Parameter Optimisation to Include Stability and Cost.” In Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III 10, 102–13. Springer, 2017.

Liu, Gaoyuan, Huiqi Zhao, Fang Fan, Gang Liu, Qiang Xu, and Shah Nazir. “An Enhanced Intrusion Detection Model Based on Improved kNN in WSNs.” Sensors 22, no. 4 (2022): 1407.

Moosavian, A., H. Ahmadi, A. Tabatabaeefar, and M. Khazaee. “Comparison of Two Classifiers; K-Nearest Neighbor and Artificial Neural Network, for Fault Diagnosis on a Main Engine Journal-Bearing.” Shock and Vibration 20, no. 2 (2013): 263–72.

Morizet, Nicolas, Nathalie Godin, J. Tang, E. Maillet, Marion Fregonese, and Bernard Normand. “Classification of Acoustic Emission Signals Using Wavelets and Random Forests: Application to Localized Corrosion.” Mechanical Systems and Signal Processing 70 (2016): 1026–37.

Rehman, Muhammad Habib ur, Ibrar Yaqoob, Khaled Salah, Muhammad Imran, Prem Prakash Jayaraman, and Charith Perera. “The Role of Big Data Analytics in Industrial Internet of Things.” Future Generation Computer Systems 99 (2019): 247–59.

Runkler, Thomas A. Data Analytics. Springer, 2020.

Santur, Yunus, Mehmet Karaköse, and Erhan Akin. “Random Forest Based Diagnosis Approach for Rail Fault Inspection in Railways.” In 2016 National Conference on Electrical, Electronics and Biomedical Engineering (ELECO), 745–50. IEEE, 2016.

Wang, Binquan, Geng Huangfu, Zhipeng Zheng, and Yiping Guo. “Giant Electric Field-Induced Strain with High Temperature-Stability in Textured KNN-Based Piezoceramics for Actuator Applications.” Advanced Functional Materials, 2023, 2214643.

Wang, JunPing, WenSheng Zhang, YouKang Shi, ShiHui Duan, and Jin Liu. “Industrial Big Data Analytics: Challenges, Methodologies, and Applications.” arXiv Preprint arXiv:1807.01016, 2018.

Yang, Zeyu, and Zhiqiang Ge. “On Paradigm of Industrial Big Data Analytics: From Evolution to Revolution.” IEEE Transactions on Industrial Informatics 18, no. 12 (2022): 8373–88.

Zermane, Hanane, and Abbes Drardja. “Development of an Efficient Cement Production Monitoring System Based on the Improved Random Forest Algorithm.” The International Journal of Advanced Manufacturing Technology 120, no. 3-4 (2022): 1853–66.

Zhou, Shiyu, and Yong Chen. Industrial Data Analytics for Diagnosis and Prognosis: A Random Effects Modelling Approach. John Wiley & Sons, 2021.