Dataset related to the Journal Article 'A deep learning method for the prediction of ship fuel consumption in real operational conditions'

Mingyang Zhang (Other)
Nikolaos Tsoulakos (Creator)
Pentti Kujala (Contributor)
Spyros Hirdaris (American Bureau of Shipping, Greece) (Contributor)

Dataset

Description

This dataset contains the data used to plot the graphs and create tables corresponding to the figure/table number in the published version of the paper. Paper DOI:https://doi.org/10.1016/j.engappai.2023.107425

Date made available	27 Apr 2024
Publisher	Zenodo

Dataset Licences

CC-BY-4.0

DOI
10.5281/zenodo.13846854

Access Dataset

open

1 Article

A deep learning method for the prediction of ship fuel consumption in real operational conditions
Zhang, M., Tsoulakos, N., Kujala, P. & Hirdaris, S., 1 Apr 2024, In: Engineering Applications of Artificial Intelligence. 130, 21 p., 107425.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
93 Citations (Scopus)

1026 Downloads (Pure)

1 Active

RETROFIT55: Retrofit solutions to achieve 55% ghg reduction by 2030
Remes, H. (Principal investigator), Shademani, R. (Project Member), Manderbacka, T. (Project Member), Zhang, M. (Project Member), Hirdaris, S. (Project Member), Tavakoli, S. (Project Member), Mikkola, T. (Project Member), Kondratenko, A. (Project Member) & Yan, D. (Project Member)
01/01/2023 → 31/12/2025
Project: EU_HEFWP

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