relation: https://khub.utp.edu.my/scholars/11329/
title: Survey of Sea Wave Parameters Classification and Prediction using Machine Learning Models
creator: Umair, M.
creator: Hashmani, M.A.
creator: Hasan, M.H.B.
description: Sea has always played a pivotal role in human life. It formulates the weather, provides transportation medium, food, natural resources like oil and gas, and much more. Countless commercial and industrial activities take place on the surface of the sea, thus understanding, classifying and predicting the sea surface wave is a topic of great interest. Many numerical models (NM) have been proposed to model the behavior of sea waves, however, they are complex and costly for site-specific studies. On the other hand, data-driven machine learning (ML) models have recently proved to be an effective solution for site-specific classification, real-time or near-future prediction problems. The ML approach utilizes marine datasets to train, test and validate the model. In this paper, we present a survey of ML studies on the topic of classification and prediction of sea wave parameters. We hope that this paper provides a holistic model-based view to new researchers and pave the path for future research. © 2019 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2019
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Umair, M. and Hashmani, M.A. and Hasan, M.H.B.  (2019) Survey of Sea Wave Parameters Classification and Prediction using Machine Learning Models.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079353118&doi=10.1109%2fAiDAS47888.2019.8970706&partnerID=40&md5=771e5927f59ccee36e63d7f736eaeda3
relation: 10.1109/AiDAS47888.2019.8970706
identifier: 10.1109/AiDAS47888.2019.8970706