Articles | Volume 16, issue 11
https://doi.org/10.5194/hess-16-4417-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-16-4417-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
26 Nov 2012
A hybrid model of self organizing maps and least square support vector machine for river flow forecasting
S. Ismail
Department of Mathematics, Science Faculty, Universiti Teknologi Malaysia, Malaysia
A. Shabri
Department of Software Engineering, Faculty of Computer Science and Information System, Universiti Teknologi Malaysia, Malaysia
R. Samsudin
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Cited
28 citations as recorded by crossref.
- Comment on "A hybrid model of self organizing maps and least square support vector machine for river flow forecasting" by Ismail et al. (2012) F. Fahimi & A. El-Shafie 10.5194/hess-18-2711-2014
- Univariate streamflow forecasting using commonly used data-driven models: literature review and case study Z. Zhang et al. 10.1080/02626667.2018.1469756
- A novel prediction model of PM2.5 mass concentration based on back propagation neural network algorithm Y. Chen et al. 10.3233/JIFS-179119
- The Application of a Hybrid Model Using Mathematical Optimization and Intelligent Algorithms for Improving the Talc Pellet Manufacturing Process D. Buntam et al. 10.3390/sym12101602
- Using self-organizing maps to infill missing data in hydro-meteorological time series from the Logone catchment, Lake Chad basin E. Nkiaka et al. 10.1007/s10661-016-5385-1
- The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management V. Kumar et al. 10.3390/su151310543
- A New Approach for Modeling Sediment-Discharge Relationship: Local Weighted Linear Regression O. Kisi & C. Ozkan 10.1007/s11269-016-1481-9
- Determination of Surface and Hole Quality in Drilling of AISI D2 Cold Work Tool Steel Using MPMR, MARS and LSSVM P. Samui 10.1142/S0219686714500140
- NOVEL APPROACH TO IMPROVE GEOCENTRIC TRANSLATION MODEL PERFORMANCE USING ARTIFICIAL NEURAL NETWORK TECHNOLOGY Y. Ziggah et al. 10.1590/s1982-21702017000100014
- Machine learning and regression-based techniques for predicting sprinkler irrigation's wind drift and evaporation losses M. Mattar et al. 10.1016/j.agwat.2022.107529
- SOM-Based Decision Support System for Reservoir Operation Management R. Rodríguez-Alarcón & S. Lozano 10.1061/(ASCE)HE.1943-5584.0001496
- A hybrid forecasting model based on the group method of data handling and wavelet decomposition for monthly rivers streamflow data sets W. Shaikh et al. 10.1515/phys-2022-0066
- Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS M. Goyal et al. 10.1016/j.eswa.2014.02.047
- Development of a coupled wavelet transform and evolutionary Levenberg‐Marquardt neural networks for hydrological process modeling P. Abbaszadeh et al. 10.1111/coin.12124
- Monthly Streamflow Modeling Based on Self-Organizing Maps and Satellite-Estimated Rainfall Data T. do Nascimento et al. 10.1007/s11269-022-03147-8
- Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map E. Lee & S. Kim 10.5194/hess-25-5733-2021
- Wavelet Decomposition Impacts on Traditional Forecasting Time Series Models W. A. Shaikh et al. 10.32604/cmes.2022.017822
- Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm Y. Tikhamarine et al. 10.1016/j.jhydrol.2019.124435
- Capability of Artificial Neural Network for Forward Conversion of Geodetic Coordinates $$(\phi ,\lambda ,h)$$ ( ϕ , λ , h ) to Cartesian Coordinates (X, Y, Z) Y. Ziggah et al. 10.1007/s11004-016-9638-x
- A Novel LSSVM Based Algorithm to Increase Accuracy of Bacterial Growth Modeling M. Salehi Borujeni et al. 10.21859/ijb.1542
- Self-organizing maps by difference of convex functions optimization H. Le Thi & M. Nguyen 10.1007/s10618-014-0369-7
- The municipal solid waste generation distribution prediction system based on FIG–GA-SVR model F. Dai et al. 10.1007/s10163-020-01022-5
- Towards Safer Data-Driven Forecasting of Extreme Streamflows J. Matos et al. 10.1007/s11269-017-1834-z
- Reply to the “Discussion by Haddad et al. on ‘Hydroclimatic stream flow prediction using least square-support vector regression’ by Bhagwat and Maity (2013)” P. Bhagwat & R. Maity 10.1080/09715010.2014.881075
- River Stage Forecasting Using Wavelet Packet Decomposition and Machine Learning Models Y. Seo et al. 10.1007/s11269-016-1409-4
- Modeling River Stream Flow Using Support Vector Machine A. Rafidah & Y. Suhaila 10.4028/www.scientific.net/AMM.315.602
- Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons Z. Yaseen et al. 10.1007/s11269-018-1909-5
- Investigating the application of artificial intelligence for earthquake prediction in Terengganu S. Marhain et al. 10.1007/s11069-021-04716-7
25 citations as recorded by crossref.
- Comment on "A hybrid model of self organizing maps and least square support vector machine for river flow forecasting" by Ismail et al. (2012) F. Fahimi & A. El-Shafie 10.5194/hess-18-2711-2014
- Univariate streamflow forecasting using commonly used data-driven models: literature review and case study Z. Zhang et al. 10.1080/02626667.2018.1469756
- A novel prediction model of PM2.5 mass concentration based on back propagation neural network algorithm Y. Chen et al. 10.3233/JIFS-179119
- The Application of a Hybrid Model Using Mathematical Optimization and Intelligent Algorithms for Improving the Talc Pellet Manufacturing Process D. Buntam et al. 10.3390/sym12101602
- Using self-organizing maps to infill missing data in hydro-meteorological time series from the Logone catchment, Lake Chad basin E. Nkiaka et al. 10.1007/s10661-016-5385-1
- The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management V. Kumar et al. 10.3390/su151310543
- A New Approach for Modeling Sediment-Discharge Relationship: Local Weighted Linear Regression O. Kisi & C. Ozkan 10.1007/s11269-016-1481-9
- Determination of Surface and Hole Quality in Drilling of AISI D2 Cold Work Tool Steel Using MPMR, MARS and LSSVM P. Samui 10.1142/S0219686714500140
- NOVEL APPROACH TO IMPROVE GEOCENTRIC TRANSLATION MODEL PERFORMANCE USING ARTIFICIAL NEURAL NETWORK TECHNOLOGY Y. Ziggah et al. 10.1590/s1982-21702017000100014
- Machine learning and regression-based techniques for predicting sprinkler irrigation's wind drift and evaporation losses M. Mattar et al. 10.1016/j.agwat.2022.107529
- SOM-Based Decision Support System for Reservoir Operation Management R. Rodríguez-Alarcón & S. Lozano 10.1061/(ASCE)HE.1943-5584.0001496
- A hybrid forecasting model based on the group method of data handling and wavelet decomposition for monthly rivers streamflow data sets W. Shaikh et al. 10.1515/phys-2022-0066
- Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS M. Goyal et al. 10.1016/j.eswa.2014.02.047
- Development of a coupled wavelet transform and evolutionary Levenberg‐Marquardt neural networks for hydrological process modeling P. Abbaszadeh et al. 10.1111/coin.12124
- Monthly Streamflow Modeling Based on Self-Organizing Maps and Satellite-Estimated Rainfall Data T. do Nascimento et al. 10.1007/s11269-022-03147-8
- Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map E. Lee & S. Kim 10.5194/hess-25-5733-2021
- Wavelet Decomposition Impacts on Traditional Forecasting Time Series Models W. A. Shaikh et al. 10.32604/cmes.2022.017822
- Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm Y. Tikhamarine et al. 10.1016/j.jhydrol.2019.124435
- Capability of Artificial Neural Network for Forward Conversion of Geodetic Coordinates $$(\phi ,\lambda ,h)$$ ( ϕ , λ , h ) to Cartesian Coordinates (X, Y, Z) Y. Ziggah et al. 10.1007/s11004-016-9638-x
- A Novel LSSVM Based Algorithm to Increase Accuracy of Bacterial Growth Modeling M. Salehi Borujeni et al. 10.21859/ijb.1542
- Self-organizing maps by difference of convex functions optimization H. Le Thi & M. Nguyen 10.1007/s10618-014-0369-7
- The municipal solid waste generation distribution prediction system based on FIG–GA-SVR model F. Dai et al. 10.1007/s10163-020-01022-5
- Towards Safer Data-Driven Forecasting of Extreme Streamflows J. Matos et al. 10.1007/s11269-017-1834-z
- Reply to the “Discussion by Haddad et al. on ‘Hydroclimatic stream flow prediction using least square-support vector regression’ by Bhagwat and Maity (2013)” P. Bhagwat & R. Maity 10.1080/09715010.2014.881075
- River Stage Forecasting Using Wavelet Packet Decomposition and Machine Learning Models Y. Seo et al. 10.1007/s11269-016-1409-4
3 citations as recorded by crossref.
- Modeling River Stream Flow Using Support Vector Machine A. Rafidah & Y. Suhaila 10.4028/www.scientific.net/AMM.315.602
- Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons Z. Yaseen et al. 10.1007/s11269-018-1909-5
- Investigating the application of artificial intelligence for earthquake prediction in Terengganu S. Marhain et al. 10.1007/s11069-021-04716-7
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