| DOI: | 10.1016/j.gloplacha.2014.07.002
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| 论文题名: | Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming |
| 作者: | Imani M.; You R.-J.; Kuo C.-Y.
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| ISSN: | 0921-8504
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| 出版年: | 2014
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| 卷: | 121 | | 起始页码: | 53
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| 结束页码: | 63
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| 语种: | 英语
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| 英文关键词: | Caspian Sea level
; Gene expression programming
; Satellite altimetry
; Support vector machine
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| Scopus关键词: | Algorithms
; Aneroid altimeters
; Forecasting
; Gene expression
; Mean square error
; Neural networks
; Satellites
; Sea level
; Water management
; Cascade correlation neural networks
; Caspian sea
; Coefficient of determination
; Gene expression programming
; Satellite altimetry
; Satellite altimetry data
; Support vector regression algorithms
; Water supply management
; Support vector machines
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| 英文摘要: | Sea level forecasting at various time intervals is of great importance in water supply management. Evolutionary artificial intelligence (AI) approaches have been accepted as an appropriate tool for modeling complex nonlinear phenomena in water bodies. In the study, we investigated the ability of two AI techniques: support vector machine (SVM), which is mathematically well-founded and provides new insights into function approximation, and gene expression programming (GEP), which is used to forecast Caspian Sea level anomalies using satellite altimetry observations from June 1992 to December 2013. SVM demonstrates the best performance in predicting Caspian Sea level anomalies, given the minimum root mean square error (RMSE=0.035) and maximum coefficient of determination (R2=0.96) during the prediction periods. A comparison between the proposed AI approaches and the cascade correlation neural network (CCNN) model also shows the superiority of the GEP and SVM models over the CCNN. © 2014 Elsevier B.V. |
| URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904748430&doi=10.1016%2fj.gloplacha.2014.07.002&partnerID=40&md5=a2fe67771ae841bd3e49c39e839c9caa
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/11410
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| Appears in Collections: | 全球变化的国际研究计划
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作者单位: | Department of Geomatics, National Cheng Kung University, No. 1 University Road, Tainan 701, Taiwan
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| Recommended Citation: | |
Imani M.,You R.-J.,Kuo C.-Y.. Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming[J],2014-01-01,121.
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