References
- [BS] British Standard. 2012. Condition monitoring and diagnostics of machines. BS ISO 13372:2012. London: British Standards Institution; p. 28.
- Curry B, Morgan PH. 2004. Evaluating Kohonen's learning rule: an approach through genetic algorithms. Eur J Oper Res. 154:191–205.
- Hagenauer J, Helbich M. 2013. Hierarchical self-organizing maps for clustering spatiotemporal data. Int J Geogra Inform Sci. 27:2026–2042.
- Haykin S. 1998. Neural networks: a comprehensive foundation. Delhi: Prentice Hall PTR.
- INCASS. 2015. Deliverable D5.4 ‘Data exchange’. Glasgow (UK): INCASS-Inspection Capabilities for Enhanced Ship Safety.
- Jain AK. 2010. Data clustering: 50 years beyond K-means. Pattern Recogn Lett. 31:651–666.
- Jardine AKS, Lin D, Banjevic D. 2006. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech Syst Signal Process. 20:1483–1510.
- Jung Y, Park H, Du D-Z, Drake BL. 2003. A decision criterion for the optimal number of clusters in hierarchical clustering. J Global Optim. 25:91–111.
- Kobbacy KAH, Murthy DP. 2008. Complex system maintenance handbook. London: Springer Science & Business Media.
- Kohonen T. 1998. The self-organizing map. Neurocomputing. 21:1–6.
- Kohonen T. 2013. Essentials of the self-organizing map. Neural Netw. 37:52–65.
- Lazakis I, Ölçer A. 2015. Selection of the best maintenance approach in the maritime industry under fuzzy multiple attributive group decision-making environment. Proc Inst Mech Eng. 230(2):297–309.
- Namratha M, Prajwala T. 2012. A comprehensive overview of clustering algorithms in pattern recognition. IOR J Comput Eng. 4(6):23–30.
- Pascual DG. 2015. Artificial intelligence tools: decision support systems in condition monitoring and diagnosis. London: CRC Press.
- Raza J, Liyanage JP. 2009. Application of intelligent technique to identify hidden abnormalities in a system: A case study from oil export pumps from an offshore oil production facility. J Qual Maint Eng. 15:221–235.
- Stephens M. 2017. Future operating costs report. London: MS LLP.
- Stopford M. 2009. Maritime economics 3e. New York (NY): Routledge.
- Tinsley D. 2016. Dawning of new era in asset maintenance. London (UK). Marine Power & Propulsion Supplement 2016. Sect. 1 (col. 4).
- Ultsch A, Vetter C, Vetter C. 1995. Self-organizing-feature-maps versus statistical clustering methods: a benchmark Marburg. Marburg: University of Marburg.
- Vesanto J, Alhoniemi E. 2000. Clustering of the self-organizing map. IEEE Trans Neural Netw. 11:586–600.
- Xu R, Wunsch DC. 2010. Clustering algorithms in biomedical research: a review. IEEE Rev Biomed Eng. 3:120–154.
- Yan J. 2014. Machinery prognostics and prognosis oriented maintenance management. New Jersey: Wiley.