One Class Classification Based Anomaly Detection for Marine Engines

Abstract

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.

SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets

“…It is also noteworthy that some studies develop the effect of missing data on their predictions due to data collection on this type of platform [55][56][57]. One class of SVM models [58,59] is of special relevance and application in naval assets PdM.…”