A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.

Ship collision accidents are the primary threat to traffic safety in the sea. Collision accidents can cause casualties and environmental pollution. The collision risk is a major indicator for navigators and surveillance operators to judge the collision danger between meeting ships. The number of col...

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Autores principales:	Tian Chai, Han Xue
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/35437b17f5a44db293d6a1f2da962b16
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spelling	oai:doaj.org-article:35437b17f5a44db293d6a1f2da962b162021-12-02T20:11:23ZA study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.1932-620310.1371/journal.pone.0250948https://doaj.org/article/35437b17f5a44db293d6a1f2da962b162021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0250948https://doaj.org/toc/1932-6203Ship collision accidents are the primary threat to traffic safety in the sea. Collision accidents can cause casualties and environmental pollution. The collision risk is a major indicator for navigators and surveillance operators to judge the collision danger between meeting ships. The number of collision accidents per unit time in a certain water area can be considered to describe the regional collision risk However, historical ship collision accidents have contingencies, small sample sizes and weak regularities; hence, ship collision conflicts can be used as a substitute for ship collision accidents in characterizing the maritime traffic safety situation and have become an important part of methods that quantitatively study the traffic safety problem and its countermeasures. In this work, an EMD-QPSO-LSSVM approach, which is a hybrid of empirical mode decomposition (EMD) and quantum-behaved particle swarm optimization (QPSO) optimized least squares support vector machine (LSSVM) model, is proposed to forecast ship collision conflicts. First, original ship collision conflict time series are decomposed into a collection of intrinsic mode functions (IMFs) and a residue with EMD. Second, both the IMF components and residue are applied to establish the corresponding LSSVM models, where the key parameters of the LSSVM are optimized by QPSO algorithm. Then, each subseries is predicted with the corresponding LSSVM. Finally, the prediction values of the original ship collision conflict datasets are calculated by the sum of the forecasting values of each subseries. The prediction results of the proposed method is compared with GM, Lasso regression method, EMD-ENN, and the predicted results indicate that the proposed method is efficient and can be used for the ship collision conflict prediction.Tian ChaiHan XuePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0250948 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tian Chai Han Xue A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.
description	Ship collision accidents are the primary threat to traffic safety in the sea. Collision accidents can cause casualties and environmental pollution. The collision risk is a major indicator for navigators and surveillance operators to judge the collision danger between meeting ships. The number of collision accidents per unit time in a certain water area can be considered to describe the regional collision risk However, historical ship collision accidents have contingencies, small sample sizes and weak regularities; hence, ship collision conflicts can be used as a substitute for ship collision accidents in characterizing the maritime traffic safety situation and have become an important part of methods that quantitatively study the traffic safety problem and its countermeasures. In this work, an EMD-QPSO-LSSVM approach, which is a hybrid of empirical mode decomposition (EMD) and quantum-behaved particle swarm optimization (QPSO) optimized least squares support vector machine (LSSVM) model, is proposed to forecast ship collision conflicts. First, original ship collision conflict time series are decomposed into a collection of intrinsic mode functions (IMFs) and a residue with EMD. Second, both the IMF components and residue are applied to establish the corresponding LSSVM models, where the key parameters of the LSSVM are optimized by QPSO algorithm. Then, each subseries is predicted with the corresponding LSSVM. Finally, the prediction values of the original ship collision conflict datasets are calculated by the sum of the forecasting values of each subseries. The prediction results of the proposed method is compared with GM, Lasso regression method, EMD-ENN, and the predicted results indicate that the proposed method is efficient and can be used for the ship collision conflict prediction.
format	article
author	Tian Chai Han Xue
author_facet	Tian Chai Han Xue
author_sort	Tian Chai
title	A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.
title_short	A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.
title_full	A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.
title_fullStr	A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.
title_full_unstemmed	A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.
title_sort	study on ship collision conflict prediction in the taiwan strait using the emd-based lssvm method.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/35437b17f5a44db293d6a1f2da962b16
work_keys_str_mv	AT tianchai astudyonshipcollisionconflictpredictioninthetaiwanstraitusingtheemdbasedlssvmmethod AT hanxue astudyonshipcollisionconflictpredictioninthetaiwanstraitusingtheemdbasedlssvmmethod AT tianchai studyonshipcollisionconflictpredictioninthetaiwanstraitusingtheemdbasedlssvmmethod AT hanxue studyonshipcollisionconflictpredictioninthetaiwanstraitusingtheemdbasedlssvmmethod
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A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.

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