Ship performance monitoring using machine-learning

Statistical modeling of Ship’s hydrodynamic performance indicator

(2021) Prateek Gupta et al.   APPLIED OCEAN RESEARCH

Uncertainty in the real-time estimation of ship speed through water

(2021) Øyvind Øksnes Dalheim et al.   OCEAN ENGINEERING

Comparison of added resistance methods using digital twin and full-scale data

(2021) Bhushan Taskar et al.   OCEAN ENGINEERING

Regression analysis of experimental data for added resistance in waves of arbitrary heading and development of a semi-empirical formula

(2020) Shukui Liu et al.   OCEAN ENGINEERING

A novelty detection approach to diagnosing hull and propeller fouling

(2019) Andrea Coraddu et al.   OCEAN ENGINEERING

Data-driven ship digital twin for estimating the speed loss caused by the marine fouling

(2019) Andrea Coraddu et al.   OCEAN ENGINEERING

New approach to monitoring hull condition of ships as objective for selecting optimal docking period

(2018) Žarko Koboević et al.   Ships and Offshore Structures

A marine biofilm flow cell for in situ screening marine fouling control coatings using optical coherence tomography

(2018) Stefania Fabbri et al.   OCEAN ENGINEERING

Ship Hull Fouling Estimation Using Shipboard Measurements, Models for Resistance Components, and Shaft Torque Calculation Using Engine Model

(2017) Michael I. Foteinos et al.   JOURNAL OF SHIP RESEARCH

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS