Abstract
BP algorithm is the typical supervised learning algorithm, so neural network cannot be trained on-line by it. For this reason, a new algorithm (TD-DBP), which was composed of temporal difference (TD) method and dynamic BP algorithm (DBP), was proposed to overcome the restriction. TD-DBP algorithm can make Elman network train on-line incrementally. The gradient descent momentum and adaptive learning rate TD-DBP algorithm can improve the training speed and stability of Elman network effectively. Using the collected real time data, the modified TD-DBP algorithm was able to realize direct multi-step predictions for generalized heave motion of wave compensating platform.
Original language | English |
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Title of host publication | 3rd International Symposium on Intelligent Information Technology Application Workshops, IITAW 2009 |
Pages | 460-463 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 1 Dec 2009 |
Externally published | Yes |
Event | 3rd International Symposium on Intelligent Information Technology Application Workshops, IITAW 2009 - NanChang, China Duration: 21 Nov 2009 → 22 Nov 2009 |
Conference
Conference | 3rd International Symposium on Intelligent Information Technology Application Workshops, IITAW 2009 |
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Country/Territory | China |
City | NanChang |
Period | 21/11/09 → 22/11/09 |
Keywords
- Generalized heave motion
- Wave compensating Elman neural network
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications