32 Chapter 1. Introduction Yin, Z., A. S. Leon, A. Sharifi, and M. H. Amini (n.d.). “Optimal Control of Combined Sewer Systems to Minimize Sewer Overflows by Using Reinforcement Learning”. In: World Environmental and Water Resources Congress 2023, pp. 711–722. doi: 10.1061/ 9780784484852.067. Zeng, X., Z. Wang, H. Wang, S. Zhu, and S. Chen (2023). “Progress in Drainage Pipeline Condition Assessment and Deterioration Prediction Models”. In: Sustainability 15.4, p. 3849. doi: 10.3390/su15043849. Zhang, J. and J. Lee (2011). “A review on prognostics and health monitoring of Li-ion battery”. In: Journal of Power Sources 196.15, pp. 6007–6014. issn: 0378-7753. doi: 10.1016/j.jpowsour.2011.03.101. Zhang, L., J. Lin, B. Liu, Z. Zhang, X. Yan, and M. Wei (2019). “A Review on Deep Learning Applications in Prognostics and Health Management”. In: IEEE Access 7, pp. 162415–162438. doi: 10.1109/ACCESS.2019.2950985. Zhang, W., D. Yang, and H. Wang (2019). “Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey”. In: IEEE Systems Journal 13.3, pp. 2213– 2227. doi: 10.1109/JSYST.2019.2905565. Zhang, X., R. Xu, C. Kwan, S. Liang, Q. Xie, and L. Haynes (2005). “An integrated approach to bearing fault diagnostics and prognostics”. In: Proceedings of the 2005, American Control Conference, 2005. 2750–2755 vol. 4. doi: 10 . 1109 / ACC . 2005 . 1470385. Zhou, D., Z. Yu, H. Zhang, and S. Weng (2016). “A novel grey prognostic model based on Markov process and grey incidence analysis for energy conversion equipment degradation”. In: Energy 109, pp. 420–429. issn: 0360-5442. doi: 10.1016/j.energy.2016. 05.008. Zhu, S.-P., H.-Z. Huang, W. Peng, H.-K. Wang, and S. Mahadevan (2016). “Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty”. In: Reliability Engineering & System Safety 146, pp. 1–12. issn: 0951-8320. doi: 10.1016/j.ress.2015.10.002. Zio, E. (2022). “Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice”. In: Reliability Engineering & System Safety 218, p. 108119. issn: 0951-8320. doi: 10.1016/j.ress.2021.108119.
RkJQdWJsaXNoZXIy MjY0ODMw