Improving Monsoon Precipitation Prediction Using Combined Convolutional and Long Short Term Memory Neural Network
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Improving Monsoon Precipitation Prediction Using Combined Convolutional and Long Short Term Memory Neural Network
Authors
Keywords
-
Journal
Water
Volume 11, Issue 5, Pages 977
Publisher
MDPI AG
Online
2019-05-09
DOI
10.3390/w11050977
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Improving Precipitation Estimation Using Convolutional Neural Network
- (2019) Baoxiang Pan et al. WATER RESOURCES RESEARCH
- A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
- (2018) Khabat Khosravi et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Is precipitation a good metric for model performance?
- (2018) Francisco J. Tapiador et al. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
- Flood Prediction Using Machine Learning Models: Literature Review
- (2018) Amir Mosavi et al. Water
- An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines
- (2018) Bahram Choubin et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Establishing a rainfall threshold for flash flood warnings in China’s mountainous areas based on a distributed hydrological model
- (2016) Qinghua Miao et al. JOURNAL OF HYDROLOGY
- Information Analysis of Catchment Hydrologic Patterns across Temporal Scales
- (2016) Baoxiang Pan et al. Advances in Meteorology
- Validation and comparison of a new gauge-based precipitation analysis over mainland China
- (2015) Yan Shen et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
- The quiet revolution of numerical weather prediction
- (2015) Peter Bauer et al. NATURE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- A distributed scheme developed for eco-hydrological modeling in the upper Heihe River
- (2014) DaWen Yang et al. Science China-Earth Sciences
- Development of a China Dataset of Soil Hydraulic Parameters Using Pedotransfer Functions for Land Surface Modeling
- (2013) Yongjiu Dai et al. JOURNAL OF HYDROMETEOROLOGY
- A nonparametric kernel regression model for downscaling multisite daily precipitation in the Mahanadi basin
- (2013) S. Kannan et al. WATER RESOURCES RESEARCH
- SVM-PGSL coupled approach for statistical downscaling to predict rainfall from GCM output
- (2011) Subimal Ghosh JOURNAL OF GEOPHYSICAL RESEARCH
- Projecting changes in future heavy rainfall events for Oahu, Hawaii: A statistical downscaling approach
- (2011) Chase W. Norton et al. JOURNAL OF GEOPHYSICAL RESEARCH
- The ERA-Interim reanalysis: configuration and performance of the data assimilation system
- (2011) D. P. Dee et al. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
- Dreary state of precipitation in global models
- (2010) Graeme L. Stephens et al. JOURNAL OF GEOPHYSICAL RESEARCH
- Role of predictors in downscaling surface temperature to river basin in India for IPCC SRES scenarios using support vector machine
- (2008) Aavudai Anandhi et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
- A Statistical Downscaling Model for Southern Australia Winter Rainfall
- (2008) Yun Li et al. JOURNAL OF CLIMATE
- Long lead monsoon rainfall prediction for meteorological sub-divisions of India using deterministic artificial neural network model
- (2008) P. Guhathakurta METEOROLOGY AND ATMOSPHERIC PHYSICS
- Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine
- (2007) Aavudai Anandhi et al. INTERNATIONAL JOURNAL OF CLIMATOLOGY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk 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