Ship Accident Prediction Based on Improved Quantum-Behaved PSO-LSSVM
Joint Authors
Sun, Kaibiao
Xue, Han
Chai, Tian
Weng, Jinxian
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-11
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Water transportation plays an important role in the comprehensive transportation system and regional logistics.
The number of vessel accidents is an important indicator for evaluating vessel traffic safety and the efficiency of the maritime management strategy.
The aim of this work is to provide an efficient way to predict the number of vessel accidents in China.
Firstly, to weaken the randomness of the vessel accident number time series, the gray processing operation is adopted to generate a new sequence with exponential and approximate exponential rules.
In addition, an extended least-squares support vector machine (LSSVM) model is applied in the forecasting of the new sequence, in which the parameters of the LSSVM are optimized by an improved quantum-behaved particle swarm (IQPSO).
The proposed method is applied in the forecasting of the number of vessel accidents in China, and the efficiency is shown by comparing the prediction results with GM (1, 1), PSO-LSSVM, and QPSO-LSSVM.
American Psychological Association (APA)
Chai, Tian& Xue, Han& Sun, Kaibiao& Weng, Jinxian. 2020. Ship Accident Prediction Based on Improved Quantum-Behaved PSO-LSSVM. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1201601
Modern Language Association (MLA)
Chai, Tian…[et al.]. Ship Accident Prediction Based on Improved Quantum-Behaved PSO-LSSVM. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1201601
American Medical Association (AMA)
Chai, Tian& Xue, Han& Sun, Kaibiao& Weng, Jinxian. Ship Accident Prediction Based on Improved Quantum-Behaved PSO-LSSVM. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1201601
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201601