Unlock instant, AI-driven research and patent intelligence for your innovation.

An identification method of ship domain model based on online self-organizing neural network

A neural network technology in the field of ships, applied in the field of revision of ship field models, which can solve problems such as lack of physical meaning and difficulty in selection

Inactive Publication Date: 2017-05-03
DALIAN MARITIME UNIVERSITY
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] There are too many pre-set parameters in the dynamic fuzzy neural network (DFNN), and these parameters lack physical meaning, so it is difficult to choose these specific parameters

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • An identification method of ship domain model based on online self-organizing neural network
  • An identification method of ship domain model based on online self-organizing neural network
  • An identification method of ship domain model based on online self-organizing neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention:

[0059] Such as Figure 1-Figure 9 Shown: An identification method of ship domain model based on online self-organizing neural network, which mainly includes the following steps:

[0060] First, select the ship safety area model, and determine the function, input variables and expected output values ​​of the model:

[0061] The ship area model adopted is the “cross-sectional area” model, where R bf , R ba and S b Represent the front and rear radius and cross-sectional radius of the area respectively, and the model is determined by the following formula:

[0062]

[0063] Among them, L, B, U represent the length, width and speed T of the ship respectively 90...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides an identification method for a model of ship domain based on an online self-organization fuzzy neural network. The method comprises the following steps of: selecting a ship safety zone model and determining a function, an input variable and a desired output value of the model of the ship safety zone model; establishing a dynamic fuzzy neural network comprising an input layer, a membership function layer, a T-norm layer and an output layer; training the dynamic fuzzy neural network by a training dataset comprising an input variable and an output value of the model till achieving accuracy requirements; and taking sailing parameters of two corresponding ships as input variables and inputting the input variables into the trained ship safety zone model so as to obtain ship safety areas of the two ships. By adopting the technical scheme, the safety model modified by using the method has better accuracy and higher safety compared with the conventional model of the ship domain.

Description

technical field [0001] The invention relates to a correction method for a ship domain model, in particular to an identification method for a ship domain model based on an online self-organizing neural network. Background technique [0002] Maritime intelligent transportation, as an important part of my country's science and technology development strategy, has gradually become an emerging cross-research hotspot for the effective integration of ship transportation and information science. And it is particularly important to study the behavior of individual ships in the marine traffic system. In the 1960s and 1970s, Kato [1] of Japan proposed the concept of the field of ship navigation safety. It can be seen from the literature [2] [3] [4] [5] that researchers have proposed various shapes and sizes of ships. Navigation Safety Domain Model. It has a wide range of applications in the field of modern ships. However, it has not been possible to form a unified model. The main re...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/02
Inventor 王宁刘刚健董诺汪旭明孟凡超孙树蕾
Owner DALIAN MARITIME UNIVERSITY