APPLICATION OF AN ARTIFICIAL NEURAL NETWORK AND MULTIPLE NONLINEAR REGRESSION TO ESTIMATE CONTAINER SHIP LENGTH BETWEEN PERPENDICULARS

被引：11

作者：

Cepowski, Tomasz ^{[1
]}

Chorab, Pawel ^{[1
]}

Lozowicka, Dorota ^{[1
]}

机构：

[1] Akad Morska Szczecinie, W Chrobrego 1-2, PL-70500 Szczecin, Poland

来源：

POLISH MARITIME RESEARCH | 2021年 / 28卷 / 02期

关键词：

ship design; ANN; regression; container ship; length; DESIGN;

D O I：

10.2478/pomr-2021-0019

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

Container ship length was estimated using artificial neural networks (ANN), as well as a random search based on Multiple Nonlinear Regression (MNLR). Two alternative equations were developed to estimate the length between perpendiculars based on container number and ship velocity using the aforementioned methods and an up-to-date container ship database. These equations could have practical applications during the preliminary design stage of a container ship. The application of heuristic techniques for the development of a MNLR model by variable and function randomisation leads to the automatic discovery of equation sets. It has been shown that an equation elaborated using this method, based on a random search, is more accurate and has a simpler mathematical form than an equation derived using ANN.

引用

页码：36 / 45

页数：10

共 27 条

[1]

Abramowski T, 2013, NAV ENG J, V125, P101

[2] Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada [J].

Adamowski, Jan ;

Chan, Hiu Fung ;

Prasher, Shiv O. ;

Ozga-Zielinski, Bogdan ;

Sliusarieva, Anna .

WATER RESOURCES RESEARCH, 2012, 48

[3] Design of a robust neural network structure for determining initial stability particulars of fishing vessels [J].

Alkan, AD ;

Gulez, K ;

Yilmaz, H .

OCEAN ENGINEERING, 2004, 31 (5-6) :761-777

[4]

Andrews D. J., 1985, INTEGRATED APPROACH

[5]

Bishop CM, 1995, NEURAL NETWORKS PATT, P477

[6]

Cepowski T, NDCURVEMASTER N DIME

[7] The prediction of ship added resistance at the preliminary design stage by the use of an artificial neural network [J].

Cepowski, Tomasz .

OCEAN ENGINEERING, 2020, 195 (195)

[8]

Chadzynski W., 2001, Scientific Reports of Szczecin University of Technology

[9]

Cheng X, 2017, PROCEEDINGS OF THE ASME 36TH INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING, 2017, VOL 1

[10] Predictions of oil/chemical tanker main design parameters using computational intelligence techniques [J].

Ekinci, S. ;

Celebi, U. B. ;

Bal, M. ;

Amasyali, M. F. ;

Boyaci, U. K. .

APPLIED SOFT COMPUTING, 2011, 11 (02) :2356-2366

← 1 2 3 →