Prediction and optimisation of fuel consumption for inland ships considering real-time status and environmental factors
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Prediction and optimisation of fuel consumption for inland ships considering real-time status and environmental factors
Authors
Keywords
Inland ship, Fuel consumption, Data-driven modelling, Optimisation, LSTM, RSSA
Journal
OCEAN ENGINEERING
Volume 221, Issue -, Pages 108530
Publisher
Elsevier BV
Online
2020-12-31
DOI
10.1016/j.oceaneng.2020.108530
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Genetic Algorithm Based Design Optimization of a Passive Anti-Roll Tank in a Sea Going Vessel
- (2020) Rahul Subramanian et al. OCEAN ENGINEERING
- A wavelet - Particle swarm optimization - Extreme learning machine hybrid modeling for significant wave height prediction
- (2020) Mosbeh R. Kaloop et al. OCEAN ENGINEERING
- Two-phase optimal solutions for ship speed and trim optimization over a voyage using voyage report data
- (2019) Yuquan Du et al. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
- Global impacts of recent IMO regulations on marine fuel oil refining processes and ship emissions
- (2019) Thuy Chu Van et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Machine learning estimates of plug-in hybrid electric vehicle utility factors
- (2019) David Goebel et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Machine learning models for predicting ship main engine Fuel Oil Consumption: A comparative study
- (2019) Christos Gkerekos et al. OCEAN ENGINEERING
- Optimal vessel speed and fleet size for industrial shipping services under the emission control area regulation
- (2019) Dian Sheng et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- An improved recurrent neural network for unmanned underwater vehicle online obstacle avoidance
- (2019) Changjian Lin et al. OCEAN ENGINEERING
- End-to-end navigation for Autonomous Underwater Vehicle with Hybrid Recurrent Neural Networks
- (2019) Xiaokai Mu et al. OCEAN ENGINEERING
- Model of speed optimization of oil tanker with irregular winds and waves for given route
- (2018) Xiaohe Li et al. OCEAN ENGINEERING
- Integrating multi-source maritime information to estimate ship exhaust emissions under wind, wave and current conditions
- (2018) Liang Huang et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Identifying Brain Networks at Multiple Time Scales via Deep Recurrent Neural Network
- (2018) Yan Cui et al. IEEE Journal of Biomedical and Health Informatics
- LSTM network: a deep learning approach for short-term traffic forecast
- (2017) Zheng Zhao et al. IET Intelligent Transport Systems
- Vessels fuel consumption forecast and trim optimisation: A data analytics perspective
- (2017) Andrea Coraddu et al. OCEAN ENGINEERING
- Predicting ship fuel consumption based on LASSO regression
- (2017) Shengzheng Wang et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- A multiple ship routing and speed optimization problem under time, cost and environmental objectives
- (2017) M. Wen et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- An artificial neural network based decision support system for energy efficient ship operations
- (2016) E. Bal Beşikçi et al. COMPUTERS & OPERATIONS RESEARCH
- Toward a More Realistic, Cost-Effective, and Greener Ground Movement Through Active Routing: A Multiobjective Shortest Path Approach
- (2016) Jun Chen et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Imprecise knowledge based design and development of titanium alloys for prosthetic applications
- (2016) S. Datta et al. Journal of the Mechanical Behavior of Biomedical Materials
- Real-time optimization of ship energy efficiency based on the prediction technology of working condition
- (2016) Kai Wang et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Multiobjective optimal design of friction stir welding considering quality and cost issues
- (2015) Q. Zhang et al. SCIENCE AND TECHNOLOGY OF WELDING AND JOINING
- Maritime routing and speed optimization with emission control areas
- (2015) Kjetil Fagerholt et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Ship speed optimization: Concepts, models and combined speed-routing scenarios
- (2014) Harilaos N. Psaraftis et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Sailing speed optimization for container ships in a liner shipping network
- (2012) Shuaian Wang et al. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
- A nature-inspired multi-objective optimisation strategy based on a new reduced space searching algorithm for the design of alloy steels
- (2010) Qian Zhang et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Reducing fuel emissions by optimizing speed on shipping routes
- (2009) K Fagerholt et al. JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
- Grey-box modeling of an ocean vessel for operational optimization
- (2008) Leifur Þ. Leifsson et al. SIMULATION MODELLING PRACTICE AND THEORY
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started