Monthly Streamflow Forecasting Using ELM-IPSO Based on Phase Space Reconstruction
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DOI: 10.1007/s11269-020-02631-3
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- Milan Palus & L. Pecen & D. Pivka, 1995. "Estimating Predictability: Redundancy and Surrogate Data Method," Working Papers 95-07-060, Santa Fe Institute.
- J. Vicente-Guillén & E. Ayuga-Telléz & D. Otero & J. Chávez & F. Ayuga & A. García, 2012. "Performance of a Monthly Streamflow Prediction Model for Ungauged Watersheds in Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3767-3784, October.
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Cited by:
- Rana Muhammad Adnan Ikram & Leonardo Goliatt & Ozgur Kisi & Slavisa Trajkovic & Shamsuddin Shahid, 2022. "Covariance Matrix Adaptation Evolution Strategy for Improving Machine Learning Approaches in Streamflow Prediction," Mathematics, MDPI, vol. 10(16), pages 1-30, August.
- Jihong Qu & Kun Ren & Xiaoyu Shi, 2021. "Binary Grey Wolf Optimization-Regularized Extreme Learning Machine Wrapper Coupled with the Boruta Algorithm for Monthly Streamflow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 1029-1045, February.
- Jincheng Zhou & Dan Wang & Shahab S. Band & Changhyun Jun & Sayed M. Bateni & M. Moslehpour & Hao-Ting Pai & Chung-Chian Hsu & Rasoul Ameri, 2023. "Monthly River Discharge Forecasting Using Hybrid Models Based on Extreme Gradient Boosting Coupled with Wavelet Theory and Lévy–Jaya Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(10), pages 3953-3972, August.
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Keywords
Streamflow prediction; Chaohe River basin; Chaotic dynamic characteristics; Phase space reconstruction; Extreme learning machine; Improved particle swarm optimization algorithm;All these keywords.
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