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- Vol. 7 Issue 2
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IndusMind: AI–Based Industrial Machine Monitoring and Predictive Maintenance System
Authors
1 Assistant Professor, Department of Information Technology, Er.Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India. 2 3 4 Student, Department of Information Technology, Er.Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India.
Article Information
- Published In
- Volume 7, Issue 2 (2026)
- Published Online
- March-April 2026
- Pages
- 407-414
- Article Type
- Original Article
- Check for updates
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References
1. K. P. Murphy, Machine Learning: A Probabilistic Perspective. MIT Press, 2012.
2. C. M. Bishop, Pattern Recognition and Machine Learning. Springer, 2006.
3. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning. Springer, 2009.
4. F. Pedregosa et al., “Scikit-learn: Machine Learning in Python,” Journal of Machine Learning Research, vol. 12, pp. 2825–2830, 2011.
5. D. C. Montgomery, Introduction to Statistical Quality Control, 7th ed. Wiley, 2012.
6. J. Lee, H. Davari, J. Singh, and V. Pandhare, “Industrial Big Data Analytics and Cyber-Physical Systems for Future Maintenance & Service Innovation,” Procedia CIRP, vol. 38, pp. 3–7, 2015.
7. A. Géron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd ed. O’Reilly Media, 2019.
8. S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 3rd ed. Pearson, 2010.
9. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction. MIT Press, 2018.
10. J. Brownlee, “A Gentle Introduction to Logistic Regression,” Machine Learning Mastery, 2020.
11. M. Kuhn and K. Johnson, Applied Predictive Modeling.Springer,2013.
12. M. Abadi et al., “TensorFlow: A System for Large-Scale Machine Learning,” in Proc. OSDI, 2016, pp. 265–283.
2. C. M. Bishop, Pattern Recognition and Machine Learning. Springer, 2006.
3. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning. Springer, 2009.
4. F. Pedregosa et al., “Scikit-learn: Machine Learning in Python,” Journal of Machine Learning Research, vol. 12, pp. 2825–2830, 2011.
5. D. C. Montgomery, Introduction to Statistical Quality Control, 7th ed. Wiley, 2012.
6. J. Lee, H. Davari, J. Singh, and V. Pandhare, “Industrial Big Data Analytics and Cyber-Physical Systems for Future Maintenance & Service Innovation,” Procedia CIRP, vol. 38, pp. 3–7, 2015.
7. A. Géron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd ed. O’Reilly Media, 2019.
8. S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 3rd ed. Pearson, 2010.
9. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction. MIT Press, 2018.
10. J. Brownlee, “A Gentle Introduction to Logistic Regression,” Machine Learning Mastery, 2020.
11. M. Kuhn and K. Johnson, Applied Predictive Modeling.Springer,2013.
12. M. Abadi et al., “TensorFlow: A System for Large-Scale Machine Learning,” in Proc. OSDI, 2016, pp. 265–283.
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