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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kai-ping Lin Xiao-yan Huang Wei-liang Liang Bing-lian Chen |
| Copyright Year | 2010 |
| Abstract | Following the thinking clue of the ensemble prediction in numerical weather prediction (NWP), a novel nonlinear artificial intelligence ensemble prediction (NAIEP) model for calculation wind speed of Mountain Darong in Guangxi has been developed based on the multiple neural networks with identical expected output created by using the genetic algorithm (GA) of evolutionary computation. The results show that the calculation accuracy by the nonlinear ensemble model of genetic - neural network for wind field is significantly higher than the traditional multiple linear regression model. Thus in practical application the long time sequence data of wind could be calculate according to the short time sequence data of the observation through the ANN nonlinear ensemble model, therefore this model is better practicability and popularize value for it provide the basis to research the exploitation wind resources. |
| Starting Page | 471 |
| Ending Page | 475 |
| File Size | 217884 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424468126 |
| e-ISBN | 9781424468133 |
| DOI | 10.1109/CSO.2010.13 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-05-28 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Weather forecasting ensemble prediction Artificial neural networks Evolutionary computation Predictive models wind assessment Wind forecasting neural network Genetic algorithms genetic algorithm Accuracy Wind speed Neural networks wind calculation Artificial intelligence |
| Content Type | Text |
| Resource Type | Article |
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