Stream Flow Forecasting with One Day Lead Using ʋ-Support Vector Regression

2021 ◽  
pp. 315-328
Author(s):  
Sameer Anipindiwar ◽  
Umamahesh V. Nanduri
Keyword(s):  
Support Vector Regression ◽  
Stream Flow ◽  
Support Vector

scholarly journals Calibration of SWAT and three data-driven models for monthly stream flow simulation in Maharlu Lake Basin

2021 ◽  
Author(s):  
Fatemeh Moazami Goudarzi ◽  
Amirpouya Sarraf ◽  
Hassan Ahmadi
Keyword(s):  
Machine Learning ◽  
Support Vector Regression ◽  
Computational Intelligence ◽  
Stream Flow ◽  
River Flow ◽  
Swat Model ◽  
Flow Simulation ◽  
Support Vector ◽  
Lake Basin ◽  
Computational Intelligence Methods

Abstract In this study, the performance of SWAT hydrological model and three computational intelligence methods used to simulate river flow are investigated. After collecting the data required for all models used, the calibration and validation stages were performed. Using the SWAT model and three methods of the Extreme Machine Learning (EML), the Support Vector Regression (SVR), and the Least Squares Support Vector Regression (LSSVR), Maharlu Lake Basin stream flow was simulated and the results obtained at Shiraz station were used for this study. A noise reduction filter was employed to improve the results from the computational intelligence methods, and SUFI-2 algorithm was used to analyze the uncertainty of the SWAT model. Finally, in order to evaluate the models developed and the SWAT model, three statistics (RMSE), (R²), and (NS) coefficient were used. The results indicated that the SWAT model and the machine learning models were generally appropriate tools for daily flow modeling, but the LSSVR model showed less errors in both learning and testing, with the coefficients NS = 0.997 and R² = 0.997 in the calibration stage and NS = 0.994 and R² = 0.994 in the validation stage, which prove their better performance compared to the other methods and the SWAT model.

Discussion of “Hydroclimatic stream flow prediction using least square-support vector regression”

2014 ◽  
Vol 20 (3) ◽  
pp. 274-275 ◽  
Author(s):  
Omid Bozorg Haddad ◽  
Mahyar Aboutalebi ◽  
Irene Garousi-Nejad
Keyword(s):  
Support Vector Regression ◽  
Stream Flow ◽  
Least Square ◽  
Support Vector ◽  
Flow Prediction

scholarly journals Forecasting One Day Ahead Stream Flow Using Support Vector Regression

2015 ◽  
Vol 4 ◽  
pp. 900-907 ◽  
Author(s):  
Shreenivas Londhe ◽  
Seema S. Gavraskar
Keyword(s):  
Support Vector Regression ◽  
Stream Flow ◽  
Support Vector

Local and Regional Hour-Ahead Forecasts of Solar Irradiance with Training Data Selection and Support Vector Regression

2016 ◽  
Vol 136 (12) ◽  
pp. 898-907 ◽  
Author(s):  
Joao Gari da Silva Fonseca Junior ◽  
Hideaki Ohtake ◽  
Takashi Oozeki ◽  
Kazuhiko Ogimoto
Keyword(s):  
Support Vector Regression ◽  
Solar Irradiance ◽  
Training Data ◽  
Data Selection ◽  
Support Vector ◽  
Training Data Selection

Data Analytics to Help Improve Hydraulic Fracture Geometry Prediction Using Support Vector Regression: Case Study

2020 ◽  
Author(s):  
Avinash Wesley ◽  
Bharat Mantha ◽  
Ajay Rajeev ◽  
Aimee Taylor ◽  
Mohit Dholi ◽  
...  
Keyword(s):  
Support Vector Regression ◽  
Hydraulic Fracture ◽  
Data Analytics ◽  
Support Vector ◽  
Fracture Geometry
Sign in / Sign up

Export Citation Format

Share Document