Real Time Prediction of Ship Pitch Motion Based on NARX Neural Network

被引：0

作者：

Wu Wenhao ^{[1
]}

Li Lianbo ^{[1
]}

Zhu Zhenyu ^{[1
]}

Jiao Yang ^{[1
]}

机构：

[1] Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China

来源：

PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年

基金：

国家重点研发计划;

关键词：

Ship; NARX neural network; Pitch motion prediction; BP neural network;

D O I：

10.1109/CCDC52312.2021.9602831

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to improve the accuracy of ship pitch prediction, a Nonlinear AutoRegressive with eXogenous inputs (NARX) neural network prediction model is proposed, through the introduction of non-linear meteorological data to train the neural network, so that it can obtain the optimal training effect and improve the prediction accuracy. Finally, the model is simulated and tested by using the real ship pitch data of Dalian Maritime University Teaching Experimental ship "YUKUN", and the results are compared with the Back Propagation (BP) neural network. The experimental results show that the model selected in this paper has high prediction accuracy.

引用

页码：6751 / 6755

页数：5

共 18 条

[1] Multi-step ahead forecasts for electricity prices using NARX: A new approach, a critical analysis of one-step ahead forecasts [J].

Andalib, Arash ;

Atry, Farid .

ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (03) :739-747

[2] Groundwater level prediction in Apulia region (Southern Italy) using NARX neural network [J].

Di Nunno, Fabio ;

Granata, Francesco .

ENVIRONMENTAL RESEARCH, 2020, 190

[3] INPUT OUTPUT PARAMETRIC MODELS FOR NON-LINEAR SYSTEMS .1. DETERMINISTIC NON-LINEAR SYSTEMS [J].

LEONTARITIS, IJ ;

BILLINGS, SA .

INTERNATIONAL JOURNAL OF CONTROL, 1985, 41 (02) :303-328

[4]

Li Z. F., 2002, Journal of Dalian Maritime University, P13

[5]

Liu C., 2016, CHINA SHIPPING, V11, P42

[6]

Liu Y., 1986, THEORY SHIP MOTION W

[7]

[楼梦瑶 Lou Mengyao], 2020, [中国舰船研究, Chinese Journal of Ship Research], V15, P48

[8]

Ma J., 2006, SHIP ENG, V01, P5

[9] Long-term time series prediction with the NARX network: An empirical evaluation [J].

Menezes, Jose Maria P., Jr. ;

Barreto, Guilherme A. .

NEUROCOMPUTING, 2008, 71 (16-18) :3335-3343

[10] Air catalytic biomass (PKS) gasification in a fixed-bed downdraft gasifier using waste bottom ash as catalyst with NARX neural network modelling [J].

Shahbaz, Muhammad ;

Taqvi, Syed Ali Ammar ;

Inayat, Muddasser ;

Inayat, Abrar ;

Sulaiman, Shaharin A. ;

McKay, Gordon ;

Al-Ansari, Tareq .

COMPUTERS & CHEMICAL ENGINEERING, 2020, 142

← 1 2 →