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Ship intelligent autopilot in narrow water

Ship intelligent autopilot in narrow water
Ship intelligent autopilot in narrow water
To provide a novel intelligent anti-collision decision-making support system it is necessary to facilitate a precise anti-collision information capability. In the reported research an innovative self-learning neurofuzzy network is proposed and applied to learn new information adaptively without forgetting old knowledge. To handle imprecise information a fuzzy set interpretation facility is incorporated into the network design. Additionally neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data is obtained from trial manoeuvres. This support system has been developed to help ship operators make a precise anti-collision decision, whilst simultaneously reducing the burden of bridge data processing.
intelligent anti-collision, decision-making, trial manoeuvre, self-learning system, neurofuzzy
Zhuo, Y.
3c60ea18-0341-4aca-a508-19b932c86557
Hearn, G.E.
c1b2912b-fe5c-432c-aaa4-39c5eff75178
Zhuo, Y.
3c60ea18-0341-4aca-a508-19b932c86557
Hearn, G.E.
c1b2912b-fe5c-432c-aaa4-39c5eff75178

Zhuo, Y. and Hearn, G.E. (2008) Ship intelligent autopilot in narrow water. 27th Annual Chinese Control Conference (CCC'08), Kunming, China. 16 - 18 Jul 2008. 6 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

To provide a novel intelligent anti-collision decision-making support system it is necessary to facilitate a precise anti-collision information capability. In the reported research an innovative self-learning neurofuzzy network is proposed and applied to learn new information adaptively without forgetting old knowledge. To handle imprecise information a fuzzy set interpretation facility is incorporated into the network design. Additionally neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data is obtained from trial manoeuvres. This support system has been developed to help ship operators make a precise anti-collision decision, whilst simultaneously reducing the burden of bridge data processing.

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ChineseControlConference_16-18July2008TrialManoeuvre.pdf - Version of Record
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More information

Submitted date: 4 January 2008
Published date: 16 July 2008
Venue - Dates: 27th Annual Chinese Control Conference (CCC'08), Kunming, China, 2008-07-16 - 2008-07-18
Keywords: intelligent anti-collision, decision-making, trial manoeuvre, self-learning system, neurofuzzy
Organisations: Fluid Structure Interactions Group

Identifiers

Local EPrints ID: 54794
URI: http://eprints.soton.ac.uk/id/eprint/54794
PURE UUID: 9a611b25-dd59-43aa-84be-4df2deda6cee

Catalogue record

Date deposited: 04 Aug 2008
Last modified: 15 Mar 2024 10:50

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Contributors

Author: Y. Zhuo
Author: G.E. Hearn

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