A Hybrid Model Based on Variational Mode Decomposition and Gradient Boosting Regression Tree for Monthly Runoff Forecasting
出版年份 2020 全文链接
标题
A Hybrid Model Based on Variational Mode Decomposition and Gradient Boosting Regression Tree for Monthly Runoff Forecasting
作者
关键词
-
出版物
WATER RESOURCES MANAGEMENT
Volume 34, Issue 2, Pages 865-884
出版商
Springer Science and Business Media LLC
发表日期
2020-01-07
DOI
10.1007/s11269-020-02483-x
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Hybrid forecasting model for non-stationary daily runoff series: A case study in the Han River Basin, China
- (2019) Tuo Xie et al. JOURNAL OF HYDROLOGY
- A data-driven model based on Fourier transform and support vector regression for monthly reservoir inflow forecasting
- (2018) Xiang Yu et al. Journal of Hydro-environment Research
- Assessment of extreme precipitation events and their teleconnections to El Niño Southern Oscillation, a case study in the Wei River Basin of China
- (2018) Rengui Jiang et al. ATMOSPHERIC RESEARCH
- Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices
- (2017) Salim Lahmiri IEEE Systems Journal
- Multi-site solar power forecasting using gradient boosted regression trees
- (2017) Caroline Persson et al. SOLAR ENERGY
- Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study in the Wei River Basin, China
- (2017) Lei Zou et al. WATER RESOURCES MANAGEMENT
- Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information
- (2017) Tiantian Yang et al. WATER RESOURCES RESEARCH
- Short-term wind speed and wind power prediction using hybrid empirical mode decomposition and kernel ridge regression
- (2017) Jyotirmayee Naik et al. APPLIED SOFT COMPUTING
- Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models
- (2016) Yun Bai et al. JOURNAL OF HYDROLOGY
- A new intelligent method based on combination of VMD and ELM for short term wind power forecasting
- (2016) Ali Akbar Abdoos NEUROCOMPUTING
- Utilizing RBF-NN and ANFIS Methods for Multi-Lead ahead Prediction Model of Evaporation from Reservoir
- (2016) Mohammed Falah Allawi et al. WATER RESOURCES MANAGEMENT
- Enhancing Long-Term Streamflow Forecasting and Predicting using Periodicity Data Component: Application of Artificial Intelligence
- (2016) Zaher Mundher Yaseen et al. WATER RESOURCES MANAGEMENT
- An Ensemble Empirical Mode Decomposition, Self-Organizing Map, and Linear Genetic Programming Approach for Forecasting River Streamflow
- (2016) Jonathan Barge et al. Water
- Urban Link Travel Time Prediction Based on a Gradient Boosting Method Considering Spatiotemporal Correlations
- (2016) Faming Zhang et al. ISPRS International Journal of Geo-Information
- Additive Model for Monthly Reservoir Inflow Forecast
- (2015) Yun Bai et al. JOURNAL OF HYDROLOGIC ENGINEERING
- Modeling of groundwater level fluctuations using dendrochronology in alluvial aquifers
- (2015) V. Gholami et al. JOURNAL OF HYDROLOGY
- Impact of climate change and human activities on runoff in the Weihe River Basin, China
- (2015) Jianxia Chang et al. QUATERNARY INTERNATIONAL
- A gradient boosting method to improve travel time prediction
- (2015) Yanru Zhang et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Heuristic Methods for Reservoir Monthly Inflow Forecasting: A Case Study of Xinfengjiang Reservoir in Pearl River, China
- (2015) Chun-Tian Cheng et al. Water
- Variational Mode Decomposition
- (2014) Konstantin Dragomiretskiy et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Monthly streamflow prediction using modified EMD-based support vector machine
- (2014) Shengzhi Huang et al. JOURNAL OF HYDROLOGY
- An integrated wavelet-support vector machine for groundwater level prediction in Visakhapatnam, India
- (2014) Ch. Suryanarayana et al. NEUROCOMPUTING
- A Four-Stage Hybrid Model for Hydrological Time Series Forecasting
- (2014) Chongli Di et al. PLoS One
- Wavelet Analysis-Support Vector Machine Coupled Models for Monthly Rainfall Forecasting in Arid Regions
- (2014) Qi Feng et al. WATER RESOURCES MANAGEMENT
- GA-Based Support Vector Machine Model for the Prediction of Monthly Reservoir Storage
- (2013) Jieqiong Su 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
- Multi-fault diagnosis for rolling element bearings based on ensemble empirical mode decomposition and optimized support vector machines
- (2013) Xiaoyuan Zhang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Gradient boosting machines, a tutorial
- (2013) Alexey Natekin et al. Frontiers in Neurorobotics
- Application of artificial neural networks to rainfall forecasting in Queensland, Australia
- (2012) John Abbot et al. ADVANCES IN ATMOSPHERIC SCIENCES
- Applying fuzzy grey modification model on inflow forecasting
- (2012) Yong-Huang Lin et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Rainfall-runoff modeling using least squares support vector machines
- (2012) Umut Okkan et al. ENVIRONMETRICS
- Monthly streamflow forecasting based on improved support vector machine model
- (2011) Jun Guo et al. EXPERT SYSTEMS WITH APPLICATIONS
- Evaluation of rainfall and discharge inputs used by Adaptive Network-based Fuzzy Inference Systems (ANFIS) in rainfall–runoff modeling
- (2010) Amin Talei et al. JOURNAL OF HYDROLOGY
- Development and testing of a physically based, three-dimensional model of surface and subsurface hydrology
- (2009) Marco Bittelli et al. ADVANCES IN WATER RESOURCES
- Potential of support vector regression for prediction of monthly streamflow using endogenous property
- (2009) Rajib Maity et al. HYDROLOGICAL PROCESSES
- A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series
- (2009) Wen-Chuan Wang et al. JOURNAL OF HYDROLOGY
- A working guide to boosted regression trees
- (2008) J. Elith et al. JOURNAL OF ANIMAL ECOLOGY
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