Rough sets-based prediction model for increasing safety of thermal power plants

References

• Bhangu, N. S., G. L. Pahuja, and R. Singh. 2015. Application of fault tree analysis for evaluating reliability and risk assessment of a thermal power plant. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 37 (18):2004–12. doi:10.1080/15567036.2012.664608.
   Web of Science ®Google Scholar
• Blaszczynski, J., S. Greco, and R. Slowinski. 2007. Multi-criteria classification - A new scheme for application of dominance-based decision rules. European Journal of Operational Research 3:1030–44. doi:10.1016/j.ejor.2006.03.004.
   Google Scholar
• Chemweno, P., I. Morag, M. Sheikhalishahi, L. Pintelon, P. Muchiri, and J. Wakiru. 2016. Development of a novel methodology for root cause analysis and selection of maintenance strategy for a thermal power plant: A data exploration approach. Engineering Failure Analysis 66:19–34. doi:10.1016/j.engfailanal.2016.04.001.
   Web of Science ®Google Scholar
• Dimitras, A. I., R. Slowinski, R. Susmaga, and C. Zopounidis. 1999. Business failure prediction using rough sets. European Journal of Operational Research 114 (2):263–80. doi:10.1016/S0377-2217(98)00255-0.
   Web of Science ®Google Scholar
• Düntsch, I., and G. Gediga. 2000. Rough set data analysis: A road to non-invasive knowledge discovery. Methodos 2:33–36. ISBN 190328001X.
   PubMedGoogle Scholar
• Greco, S., M. Benedetto, and R. Slowinski. 1998. New developments in the rough set approach to multi – attribute decision analysis. Bulletin of International Rough Set Society 2 (2/3):57–87.
   Google Scholar
• Guerin, T. 2015. An investigation into the cause of loss of containment from the supply of mini-bulk lubricants. Engineering Failure Analysis 54:1–12. doi:10.1016/j.engfailanal.2015.04.005.
   Web of Science ®Google Scholar
• Kucora, I., L. Radovanovic, D. Milosevic, S. Vulovic, M. Kovacevic, G. Otic, and Z. Adamovic. 2017. Increasing safety of power plant using a new model of reliability. Energy Sources, Part B 12:460–69. doi:10.1080/15567249.2016.1185481.
   Google Scholar
• Øhrn, A. 1999. Discernibility and rough sets in medicine: Tools and applications. Trondheim, Norway: Department of Computer and Information Science, Norwegian University of Science and Technology. ISBN 82-7984-014-1, ISSN 0802-6394.
   Google Scholar
• NSDS. 2010. National sustainable development strategy, official gazette of RS, No 75/2010. http://www.zurbnis.rs/zakoni/Nacionalna%20strategija%20odrzivog%20razvoja.pdf.
   Google Scholar
• Papadopoulos, Y., M. Walker, D. Parker, E. Rüde, R. Hamann, A. Uhlig, U. Grätz, and R. Lien. 2011. Engineering failure analysis and design optimisation with HiP-HOPS. Engineering Failure Analysis 18:590–608. doi:10.1016/j.engfailanal.2010.09.025.
   Web of Science ®Google Scholar
• Pawlak, Z. 1997. Rough set approach to knowledge-based decision support. European Journal of Operational Research 99:48–57. doi:10.1016/S0377-2217(96)00382-7.
   Web of Science ®Google Scholar
• Pawlak, Z., and A. Skowron. 2007. Rudiments of rough sets. Journal of Information Science 177:3–27. doi:10.1016/j.ins.2006.06.003.
   Google Scholar
• Pawlak, Z., J. Grzymala-Busse, R. Slowinski, and W. Ziarko. 1995. Rough sets. Communications of the ACM 38:89–95. doi:10.1145/219717.219791.
   Web of Science ®Google Scholar
• Pawlak, Z., and R. Słowinski. 1993. Rough set approach to multi–Attribute decision analysis. ICS Research Report 36, Warsaw University of Technology, Warsaw.
   Google Scholar
• Radovanovic, L., Z. Adamovic, and J. G. Speight. 2015. Risk analysis for increasing safety in power plants. Energy Sources, Part B 10:263–70. doi:10.1080/15567249.2010.549902.
   Google Scholar
• SDESS. 2015. Strategy development of energy sector of Serbia until 2025 with projections until 2030. http://www.parlament.gov.rs/upload/archive/files/lat/pdf/ostala_akta/2015/RS52-15%20lat.pdf.
   Google Scholar
• Shen, L., F. E. H. Tay, L. Qu, and Y. Shen. 2000. Fault diagnosis using Rough Sets Theory. Computers in Industry 43 (1):61–72. doi:10.1016/S0166-3615(00)00050-6.
   Web of Science ®Google Scholar
• Shen, L., and H. T. Loh. 2004. Applying rough sets to market timing decisions. Decision Support Systems 37 (4):583–97. doi:10.1016/S0167-9236(03)00089-7.
   Web of Science ®Google Scholar
• Skowron, A., and S. Dutta. 2018. Rough sets: Past, present, and future. Natural Computing 17:855–76. doi:10.1007/s11047-018-9700-3.
   PubMed Web of Science ®Google Scholar
• Smith, W. 2012. Root cause analysis for power plants. In Power plant maintenance book 1. lsa, ed. . Australia: Queensland.
   Google Scholar
• Vinterbo, S., and A. Øhrn. 2000. Minimal approximate hitting sets and rule templates. International Journal of Approximate Reasoning 25:123–43. doi:10.1016/S0888-613X(00)00051-7.
   Web of Science ®Google Scholar
• Wang, J. 2013. A rough set approach of mechanical fault diagnosis for five-plunger pump. Advances in Mechanical Engineering 5:1–11. doi:10.1155/2013/174987.
   Google Scholar
• Xiao, N., H.-Z. Huang, Y. Li, L. He, and T. Jin. 2011. Multiple failure modes analysis and weighted risk priority number evaluation in FMEA. Engineering Failure Analysis 18:1162–70. doi:10.1016/j.engfailanal.2011.02.004.
   Web of Science ®Google Scholar
• Yang, P. 2006. Data mining diagnosis system based on rough set theory for boilers in thermal power plants. Frontiers of Mechanical Engineering in China 1 (2):162−167. doi:10.1007/s11465-006-0017-z.
   Google Scholar