Deep evolutionary modeling of condition monitoring data in marine propulsion systems
Deep evolutionary modeling of condition monitoring data in marine propulsion systems is a scholarly work, published in 2018 in ''Soft Computing''. The main subjects of the publication include transportation engineering, condition monitoring, data mining, artificial intelligence, physical system, hydraulic machine, evolutionary algorithm, black box, propulsion, range, process, fault detection and isolation, prognostics, set, machine learning, and computer science. The study presents a deep evolutionary-based approach to optimally model and predict physical behaviors in industrial assets from operational data.