Exploring the potential of deep factorization machine and various gradient boosting models in modeling daily reference evapotranspiration in China
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Title
Exploring the potential of deep factorization machine and various gradient boosting models in modeling daily reference evapotranspiration in China
Authors
Keywords
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Journal
Arabian Journal of Geosciences
Volume 13, Issue 24, Pages -
Publisher
Springer Science and Business Media LLC
Online
2021-01-03
DOI
10.1007/s12517-020-06293-8
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Note: Only part of the references are listed.- First effort for constructing a high density photosynthetically active radiation dataset during 1961-2014 in China
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- Empirical and learning machine approaches to estimating reference evapotranspiration based on temperature data
- (2019) Matheus Mendes Reis et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
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- (2019) Zhigao Zhou et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
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- Reference evapotranspiration prediction using hybridized fuzzy model with firefly algorithm: Regional case study in Burkina Faso
- (2018) Hai Tao et al. AGRICULTURAL WATER MANAGEMENT
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- (2018) Zhigao Zhou et al. RENEWABLE ENERGY
- Temperature-based modeling of reference evapotranspiration using several artificial intelligence models: application of different modeling scenarios
- (2018) Hadi Sanikhani et al. THEORETICAL AND APPLIED CLIMATOLOGY
- Modelling reference evapotranspiration using a new wavelet conjunction heuristic method: Wavelet extreme learning machine vs wavelet neural networks
- (2018) Ozgur Kisi et al. AGRICULTURAL AND FOREST METEOROLOGY
- Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China
- (2018) Junliang Fan et al. AGRICULTURAL AND FOREST METEOROLOGY
- Daily pan evaporation modeling from local and cross-station data using three tree-based machine learning models
- (2018) Xianghui Lu et al. JOURNAL OF HYDROLOGY
- Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China
- (2018) Junliang Fan et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
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- (2017) Lunche Wang et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
- Pan evaporation modeling using six different heuristic computing methods in different climates of China
- (2017) Lunche Wang et al. JOURNAL OF HYDROLOGY
- Evaluation of several soft computing methods in monthly evapotranspiration modelling
- (2017) Siavash Gavili et al. METEOROLOGICAL APPLICATIONS
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- Artificial neural networks versus gene expression programming for estimating reference evapotranspiration in arid climate
- (2016) Mohamed A. Yassin et al. AGRICULTURAL WATER MANAGEMENT
- A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset
- (2016) Ravinesh C. Deo et al. APPLIED ENERGY
- An extreme learning machine approach for modeling evapotranspiration using extrinsic inputs
- (2016) Amit Prakash Patil et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Climate change effects on reference crop evapotranspiration across different climatic zones of China during 1956–2015
- (2016) Junliang Fan et al. JOURNAL OF HYDROLOGY
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- (2016) Lunche Wang et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Solar radiation prediction using different techniques: model evaluation and comparison
- (2016) Lunche Wang et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Periodic fluctuation of reference evapotranspiration during the past five decades: Does Evaporation Paradox really exist in China?
- (2016) Wanqiu Xing et al. Scientific Reports
- Spatiotemporal trends of reference evapotranspiration and its driving factors in the Beijing–Tianjin Sand Source Control Project Region, China
- (2015) Nan Shan et al. AGRICULTURAL AND FOREST METEOROLOGY
- Determination of the most influential weather parameters on reference evapotranspiration by adaptive neuro-fuzzy methodology
- (2015) Dalibor Petković et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
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- (2015) Ji-Long Chen et al. ENERGY CONVERSION AND MANAGEMENT
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- (2015) Shafika Sultan Abdullah et al. JOURNAL OF HYDROLOGY
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- (2015) Ozgur Kisi JOURNAL OF HYDROLOGY
- Support-Vector-Machine-Based Models for Modeling Daily Reference Evapotranspiration With Limited Climatic Data in Extreme Arid Regions
- (2015) Xiaohu Wen et al. WATER RESOURCES MANAGEMENT
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- (2014) Kushan C. Perera et al. AGRICULTURAL AND FOREST METEOROLOGY
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- (2010) Fotios Xystrakis et al. JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING
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- (2007) Sungwon Kim et al. JOURNAL OF HYDROLOGY
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