Improving Accuracy of River Flow Forecasting Using LSSVR with Gravitational Search Algorithm
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Improving Accuracy of River Flow Forecasting Using LSSVR with Gravitational Search Algorithm
Authors
Keywords
-
Journal
Advances in Meteorology
Volume 2017, Issue -, Pages 1-23
Publisher
Hindawi Limited
Online
2017-01-20
DOI
10.1155/2017/2391621
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Modeling reference evapotranspiration using three different heuristic regression approaches
- (2016) Ozgur Kisi AGRICULTURAL WATER MANAGEMENT
- Benchmarking regression algorithms for income prediction modeling
- (2016) Azamat Kibekbaev et al. INFORMATION SYSTEMS
- Evaluation of data driven models for river suspended sediment concentration modeling
- (2016) Mohammad Zounemat-Kermani et al. JOURNAL OF HYDROLOGY
- Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution
- (2016) Ozgur Kisi et al. JOURNAL OF HYDROLOGY
- The short-term forecasting of evaporation duct height (EDH) based on ARIMA model
- (2016) Shaobo Yang et al. MULTIMEDIA TOOLS AND APPLICATIONS
- A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system
- (2015) Rabindra Kumar Sahu et al. APPLIED SOFT COMPUTING
- Short-term wind power prediction based on LSSVM–GSA model
- (2015) Xiaohui Yuan et al. ENERGY CONVERSION AND MANAGEMENT
- Prediction of the properties of brines using least squares support vector machine (LS-SVM) computational strategy
- (2015) Milad Arabloo et al. Journal of the Taiwan Institute of Chemical Engineers
- Long-term runoff study using SARIMA and ARIMA models in the United States
- (2015) Mohammad Valipour METEOROLOGICAL APPLICATIONS
- Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models
- (2015) Ravinesh C. Deo et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Streamflow Forecasting and Estimation Using Least Square Support Vector Regression and Adaptive Neuro-Fuzzy Embedded Fuzzy c-means Clustering
- (2015) Ozgur Kisi WATER RESOURCES MANAGEMENT
- Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS
- (2014) Manish Kumar Goyal et al. EXPERT SYSTEMS WITH APPLICATIONS
- Monthly discharge forecasting using wavelet neural networks with extreme learning machine
- (2014) BaoJian Li et al. Science China-Technological Sciences
- A Stochastic Modelling Technique for Groundwater Level Forecasting in an Arid Environment Using Time Series Methods
- (2014) Mohammad Mirzavand et al. WATER RESOURCES MANAGEMENT
- Integrating Wavelet Analysis and BPANN to Simulate the Annual Runoff With Regional Climate Change: A Case Study of Yarkand River, Northwest China
- (2014) Jianhua Xu et al. WATER RESOURCES MANAGEMENT
- Application of seasonal SVR with chaotic gravitational search algorithm in electricity forecasting
- (2013) Fuh-Yuh Ju et al. APPLIED MATHEMATICAL MODELLING
- Runoff Estimation by Machine Learning Methods and Application to the Euphrates Basin in Turkey
- (2013) Abdullah Gokhan Yilmaz et al. JOURNAL OF HYDROLOGIC ENGINEERING
- A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region
- (2013) Zhibin He et al. JOURNAL OF HYDROLOGY
- M5 model tree application in daily river flow forecasting in Sohu Stream, Turkey
- (2013) M. Taghi Sattari et al. Water Resources
- Forecasting of Remotely Sensed Daily Evapotranspiration Data Over Nile Delta Region, Egypt
- (2013) Aris Psilovikos et al. WATER RESOURCES MANAGEMENT
- Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform
- (2012) Aman Mohammad Kalteh COMPUTERS & GEOSCIENCES
- Sales forecasting for computer wholesalers: A comparison of multivariate adaptive regression splines and artificial neural networks
- (2012) Chi-Jie Lu et al. DECISION SUPPORT SYSTEMS
- Rainfall-runoff modeling using least squares support vector machines
- (2012) Umut Okkan et al. ENVIRONMETRICS
- Streamflow forecasting using least-squares support vector machines
- (2012) Ani Shabri et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- Modeling river stage–discharge–sediment rating relation using support vector regression
- (2012) Sharad K. Jain HYDROLOGY RESEARCH
- Least squares support vector machine for modeling daily reference evapotranspiration
- (2012) Ozgur Kisi IRRIGATION SCIENCE
- Comparison of multivariate adaptive regression splines with coupled wavelet transform artificial neural networks for runoff forecasting in Himalayan micro-watersheds with limited data
- (2012) Jan Adamowski et al. JOURNAL OF HYDROINFORMATICS
- Modeling discharge-suspended sediment relationship using least square support vector machine
- (2012) Ozgur Kisi JOURNAL OF HYDROLOGY
- Forecasting performance of LS-SVM for nonlinear hydrological time series
- (2012) Seok Hwan Hwang et al. KSCE Journal of Civil Engineering
- Least square support vector machine and multivariate adaptive regression spline for modeling lateral load capacity of piles
- (2012) Pijush Samui et al. NEURAL COMPUTING & APPLICATIONS
- Comparison between linear genetic programming and M5 tree models to predict flow discharge in compound channels
- (2012) A. Zahiri et al. NEURAL COMPUTING & APPLICATIONS
- Least squares support vector machine for short-term prediction of meteorological time series
- (2012) A. Mellit et al. THEORETICAL AND APPLIED CLIMATOLOGY
- Singular Spectrum Analysis and ARIMA Hybrid Model for Annual Runoff Forecasting
- (2011) Qiang Zhang et al. WATER RESOURCES MANAGEMENT
- Data-driven models for monthly streamflow time series prediction
- (2010) C.L. Wu et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Filter modeling using gravitational search algorithm
- (2010) Esmat Rashedi et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
- (2010) Heesung Yoon et al. JOURNAL OF HYDROLOGY
- Estimating soil moisture using remote sensing data: A machine learning approach
- (2009) Sajjad Ahmad et al. ADVANCES IN WATER RESOURCES
- A hybrid neural network and ARIMA model for water quality time series prediction
- (2009) Durdu Ömer Faruk ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- GSA: A Gravitational Search Algorithm
- (2009) Esmat Rashedi et al. INFORMATION SCIENCES
- Forecasting Weekly Evapotranspiration with ARIMA and Artificial Neural Network Models
- (2009) Gorka Landeras et al. JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING
- Comparison between M5′ model tree and neural networks for prediction of significant wave height in Lake Superior
- (2009) A. Etemad-Shahidi et al. OCEAN ENGINEERING
- Estimation of Mean Annual Flood in Indian Catchments Using Backpropagation Neural Network and M5 Model Tree
- (2009) Krishna Kumar Singh et al. WATER RESOURCES MANAGEMENT
- Generalization performance of support vector machines and neural networks in runoff modeling
- (2008) Mohsen Behzad et al. EXPERT SYSTEMS WITH APPLICATIONS
- Performance of Multivariate Adaptive Regression Splines (MARS) in predicting runoff in mid-Himalayan micro-watersheds with limited data / Performances de régressions par splines multiples et adaptives (MARS) pour la prévision d'écoulement au sein de micro-bassins versants Himalayens d'altitudes intermédiaires avec peu de données
- (2008) V. N. SHARDA et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started