Yufei Wang,
Lokukaluge Prasad Channa Perera,
Bjørn-Morten Batalden
:
Kinematic motion models based vessel state estimation to support advanced ship predictors
Hadi Taghavifar,
Lokukaluge Prasad Channa Perera
:
Life cycle emission and cost assessment for LNG-retrofitted vessels: the risk and sensitivity analyses under fuel property and load variations
Hadi Taghavifar,
Lokukaluge Prasad Channa Perera
:
Data-driven modeling of energy-exergy in marine engines by supervised ANNs based on fuel type and injection angle classification
Process Safety and Environmental Protection (PSEP) 2023
ARKIV /
DOI
Tae-Eun Kim,
Lokukaluge Prasad Channa Perera,
Magne-Petter Sollid,
Bjørn-Morten Batalden,
Are Kristoffer Sydnes
:
Safety challenges related to autonomous ships in mixed navigational environments
WMU Journal of Maritime Affairs (JoMA) 2022
ARKIV /
DOI
Khanh Quang Bui,
Lokukaluge Prasad Channa Perera,
Jan Emblemsvåg
:
Life-cycle cost analysis of an innovative marine dual-fuel engine under uncertainties
Journal of Cleaner Production 2022
ARKIV /
DOI
Sivaraman Sivaraj,
Suresh Rajendran,
Lokukaluge Prasad Channa Perera
:
Data driven control based on Deep Q-Network algorithm for heading control and path following of a ship in calm water and waves
Yufei Wang,
Lokukaluge Prasad Channa Perera,
Bjørn-Morten Batalden
:
The Comparison of Two Kinematic Motion Models for Autonomous Shipping Maneuvers
The American Society of Mechanical Engineers (ASME) 2022
DOI
Hadi Taghavifar,
Lokukaluge Prasad Channa Perera
:
Life Cycle Assessment of Different Marine Fuel Types and Powertrain Configurations for Financial and Environmental Impact Assessment in Shipping
The American Society of Mechanical Engineers (ASME) 2022
DOI
Mahmood Taghavi,
Lokukaluge Prasad Channa Perera
:
Data Driven Digital Twin Applications Towards Green Ship Operations
The American Society of Mechanical Engineers (ASME) 2022
DOI
Lokukaluge Prasad Channa Perera,
Kostas Belibassakis,
Evangelos Filippas,
H D Maneesha Nishadini Premasiri
:
Advanced Data Analytics Based Hybrid Engine-Propeller Combinator Diagram for Green Ship Operations
The American Society of Mechanical Engineers (ASME) 2022
DOI
Nikolaos P. Ventikos,
Lokukaluge Prasad Channa Perera,
Panagiotis Sotiralis,
Emmanouil Annetis,
Eirini V. Stamatopoulou
:
A Life-Cycle Cost Framework for Onboard Emission Reduction Technologies: The Case of the Flapping-Foil Thruster Propulsion Innovation
The American Society of Mechanical Engineers (ASME) 2022
DOI
Khanh Quang Bui,
Lokukaluge Prasad Channa Perera,
Jan Emblemsvåg,
Halvor Schøyen
:
Life-Cycle Cost Analysis on a Marine Engine Innovation for Retrofit: A Comparative Study
The American Society of Mechanical Engineers (ASME) 2022
ARKIV /
DOI
Brian Murray,
Lokukaluge Prasad Perera
:
Proactive Collision Avoidance for Autonomous Ships: Leveraging Machine Learning to Emulate Situation Awareness
Khanh Quang Bui,
Lokukaluge Prasad Perera,
Jan Emblemsvåg
:
Development of a Life-cycle Cost Framework for Retrofitting Marine Engines towards Emission Reduction in Shipping
Khanh Quang Bui,
Lokukaluge Prasad Perera
:
Advanced data analytics for ship performance monitoring under localized operational conditions
Brian Murray,
Lokukaluge Prasad Perera
:
Deep Representation Learning-Based Vessel Trajectory Clustering for Situation Awareness in Ship Navigation
Lokukaluge Prasad Perera
:
Topological surfaces based advanced data analytics to support industrial digitalization in shipping
Lokukaluge Prasad Perera,
N P Ventikos,
Sven Rolfsen,
Anders Öster
:
Advanced Data Analytics towards Energy Efficient and Emission Reduction Retrofit Technology Integration in Shipping
International Society of Offshore & Polar Engineers 2021
Yufei Wang,
Lokukaluge Prasad Perera,
Bjørn-Morten Batalden
:
Particle Filter Based Ship State and Parameter Estimation for Vessel Maneuvers
International Society of Offshore & Polar Engineers 2021
Brian Murray,
Lokukaluge Prasad Perera
:
An AIS-based deep learning framework for regional ship behavior prediction
Reliability Engineering & System Safety 2021
ARKIV /
DOI
Brian Murray,
Lokukaluge Prasad Perera
:
Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness
Journal of Ocean Engineering and Science 2021
ARKIV /
DOI
Khanh Q. Bui,
Lokukaluge Prasad Perera
:
A Decision Support Framework for Cost-Effective and Energy Efficient Shipping
The American Society of Mechanical Engineers (ASME) 2020
DOI
Brian Murray,
Lokukaluge Prasad Perera
:
Unsupervised Trajectory Anomaly Detection for Situation Awareness in Maritime Navigation
The American Society of Mechanical Engineers (ASME) 2020
ARKIV /
DOI
Brian Murray,
Lokukaluge Prasad Perera
:
A dual linear autoencoder approach for vessel trajectory prediction using historical AIS data
Lokukaluge Prasad Perera,
Mario M. Machado,
Anders Valland,
Diego A.P. Manguinho
:
Failure intensity of offshore power plants under varying
maintenance policies
Engineering Failure Analysis 2019
ARKIV /
DOI
Lokukaluge Prasad Perera,
Brage Mo
:
Ship Performance and Navigation Information under High Dimensional Digital Models
Journal of Marine Science and Technology 2019
ARKIV /
DOI
Khanh Quang Bui,
Lokukaluge Prasad Perera
:
The Compliance Challenges in Emissions Control Regulations to Reduce Air Pollution from Shipping
IEEE (Institute of Electrical and Electronics Engineers) 2019
ARKIV /
DOI
Lokukaluge Prasad Perera,
Bjørn-Morten Batalden
:
Possible COLREGs Failures under Digital Helmsman of Autonomous Ships
IEEE (Institute of Electrical and Electronics Engineers) 2019
ARKIV /
DOI
Lokukaluge Prasad Perera,
Karen Vanessa Czachorowski
:
Decentralized System Intelligence in Data Driven Networks for Shipping Industrial Applications: Digital Models to Blockchain Technologies
IEEE (Institute of Electrical and Electronics Engineers) 2019
ARKIV /
DOI
Brian Murray,
Lokukaluge Prasad Perera
:
An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels
The American Society of Mechanical Engineers (ASME) 2019
ARKIV /
DOI
Lokukaluge Prasad Perera,
Brian Murray
:
Situation Awareness of Autonomous Ship Navigation in a Mixed Environment under Advanced Ship Predictor
The American Society of Mechanical Engineers (ASME) 2019
DOI
Lokukaluge Prasad Perera
:
Deep Learning towards Autonomous Ship Navigation and Possible COLREGs Failures
Journal of Offshore Mechanics and Arctic Engineering 2019
ARKIV /
DOI
Lokukaluge Prasad Perera
:
Autonomous Ship Navigation under Deep Learning and the challenges in COLREGs
The American Society of Mechanical Engineers (ASME) 2018
DOI
Brian Murray,
Lokukaluge Prasad Perera
:
A data-driven approach to vessel trajectory prediction for safe autonomous ship operations
IEEE (Institute of Electrical and Electronics Engineers) 2018
DOI
Lokukaluge Prasad Perera,
Brage Mo
:
Ship speed power performance under relative wind profiles in relation to sensor fault detection
Journal of Ocean Engineering and Science 2018
ARKIV /
DOI
Lokukaluge Prasad Perera,
Brage Mo
:
Ship Performance and Navigation Data Compression and Communication under Autoencoder System Architecture
Journal of Ocean Engineering and Science 2018
ARKIV /
DOI
Lokukaluge Prasad Perera,
Brage Mo
:
An overview of Data Veracity Issues in Ship Performance and
Navigation Monitoring
The American Society of Mechanical Engineers (ASME) 2018
DOI
R Pascoal,
Lokukaluge Prasad Perera,
Carlos Guedes Soares
:
Estimation of Directional Sea Spectra from Ship Motions in Sea Trials
Lokukaluge Prasad Perera,
Brage Mo
:
Marine Engine-Centered Data Analytics for Ship Performance Monitoring
Journal of Offshore Mechanics and Arctic Engineering 31. January 2017
ARKIV /
DOI
Lokukaluge Prasad Perera
:
Handling Big Data in Ship Performance and Navigation Monitoring
Royal Institution of Naval Architects 2017
Lokukaluge Prasad Perera
:
Navigation vector based ship maneuvering prediction
Brage Mo,
Christian Steinebach,
Lokukaluge Prasad Perera,
Petter Dehli,
Tow Foong Lim
:
OMAE2017-61219 Automated System for Fleet Benchmarking and Assessment of Technical Condition
The American Society of Mechanical Engineers (ASME) 2017
ARKIV /
DOI
Lokukaluge Prasad Perera,
Brage Mo
:
Development of Data Analytics in Shipping
Lokukaluge Prasad Perera,
Brage Mo
:
Machine intelligence based data handling framework for ship energy efficiency
IEEE Transactions on Vehicular Technology 05. June 2017
ARKIV /
DOI
Jan Emblemsvåg,
Arne Krokan,
Vilmar Æsøy,
Ivar Farup,
Karl Henning Halse,
Øivind Kåre Kjerstad
et al.:
Det kan ikke søkes forskingsmidler til kjernekraft: – Et sjansespill med Norges energifremtid?
Jan Emblemsvåg,
Arne Krokan,
Vilmar Æsøy,
Ivar Farup,
Karl Henning Halse,
Øivind Kåre Kjerstad
et al.:
Det kan ikke søkes forskingsmidler til kjernekraft: – Et sjansespill med Norges energifremtid?
Tae Eun Kim,
Lokukaluge Prasad Channa Perera,
Magne-Petter Sollid,
Bjørn-Morten Batalden,
Are K. Sydnes
:
Publisher Correction: Safety challenges related to autonomous ships in mixed navigational environments (WMU Journal of Maritime Affairs, (2022), 21, 2, (141-159), 10.1007/s13437-022-00277-z)
WMU Journal of Maritime Affairs (JoMA) 2022
DOI
Tae-Eun Kim,
Are Kristoffer Sydnes,
Bjørn-Morten Batalden,
Lokukaluge Prasad Channa Perera
:
Unlocking long-term safety, environmental and economic values of Maritime Autonomous Surface Ships (MASS)
WMU Journal of Maritime Affairs (JoMA) 2022
DOI
Brian Murray,
Lokukaluge Prasad Perera,
Egil Pedersen,
Henrique Murilo Gaspar
:
Machine Learning for Enhanced Maritime Situation Awareness - Leveraging Historical AIS Data for Ship Trajectory Prediction (PhD Thesis)
UiT Norges arktiske universitet 2021
FULLTEKST
Lokukaluge Prasad Perera,
Brage Mo,
Matthias P. Nowak
:
OMAE2017-61120 Visualization of Relative Wind Profiles in Relation to Actual Weather Conditions of Ship Routes
2017