Real-time prediction of waves using neural networks trained by particle swarm optimization
| Autor: | G.S. Dwarakish, Deepthi I. Gopinath |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Engineering
Artificial neural network 010505 oceanography business.industry lcsh:Ocean engineering Particle swarm optimization 020101 civil engineering 02 engineering and technology Real time prediction 01 natural sciences 0201 civil engineering Task (project management) Levenberg–Marquardt algorithm lcsh:Oceanography lcsh:TC1501-1800 lcsh:GC1-1581 Artificial intelligence Time series business Feed forward back propagation 0105 earth and related environmental sciences |
| Zdroj: | International Journal of Ocean and Climate Systems, Vol 7 (2016) |
| ISSN: | 1759-314X 1759-3131 |
| DOI: | 10.1177/1759313116642896 |
| Popis: | This work investigates the strength of artificial neural network that is trained by an optimization technique called particle swarm optimization in the task of time series prediction of weekly and monthly significant wave heights. The suggested approach has been implemented at the location of New Mangalore Port in India. Three years of wave data measured during 2005–2007 are analyzed. It is found that the network trained with the help of the particle swarm optimization produces more accurate predictions of the significant wave heights and further with lesser amount of data than the traditionally trained feed-forward back-propagation network. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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