EC-SVM approach for real-time hydrologic forecasting
By Xinying Yu, Shie-Yui Liong, Vladan Babovic. 2004
154 citations recorded by the source corpus.
Subfields: Environmental Engineering, Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/8df56e3bebdde89775f3d0544ca05c43adc8a3d4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Kwok-Wing Chau
- Lin Qiu
- Wenchao Wang
- Chun-tian Cheng
- Jianyi Lin
- Ozgur Kisi
- Hossein Bonakdari
- Isa Ebtehaj
In Global and Planetary Change
- Kwok-Wing Chau
- Chun-tian Cheng
- Lin Qiu
- Wenchao Wang
- Jianyi Lin
- Chaopeng Shen
- Hossein Bonakdari
- Isa Ebtehaj
In Water Science and Technology
- Kwok-Wing Chau
- Lin Qiu
- Chun-tian Cheng
- Wenchao Wang
- Jianyi Lin
- Ozgur Kisi
- Chaopeng Shen
- Hossein Bonakdari
Citations in the corpus
- Support vector machine applications in the field of hydrology: A review (2014, background): “[3] Y.”
- Using support vector machines for long-term discharge prediction (2006, methodology): “, 2004), the shuffled complex evolution algorithm (Yu et al., 2004), and the simulated annealing algorithms (Pai & Hong, 2005).”
- A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series (2009, methodology): “Recently, there are several methods developed to identify the parameters, such as the 403 simulated annealing algorithms (Pai and Hong, 2005), GA (Pai, 2006) and the shuffled complex 404 evolution algorithm (SCE-UA) (Lin et al., 2006; Yu et al., 2004).”