Prediction of Seasonal Rainfall with One-year Lead Time Using Climate Indices: A Wavelet Neural Network Scheme
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-021-03007-x.pdf
Reference36 articles.
1. Abdel-Kader H, Abd-El Salam M, Mohamed M (2021) Hybrid Machine Learning Model for Rainfall Forecasting. J Intell Syst 1:5–12. https://doi.org/10.5281/zenodo.3376685
2. Abtew W, Trimble P (2010) El Niño-Southern Oscillation link to South Florida hydrology and water management applications. Water Resour Manag 24:4255–71. https://doi.org/10.1007/s11269-010-9656-2
3. Babel MS, Badgujar GB, Shinde VR (2015) Using the mutual information technique to select explanatory variables in artificial neural networks for rainfall forecasting. Meteorol Appl 22:610–6. https://doi.org/10.1002/met.1495
4. Bagirov AM, Mahmood A (2018) A comparative assessment of models to predict monthly rainfall in Australia. Water Resour Manag 32:1777–94. https://doi.org/10.1007/s11269-018-1903-y
5. Box GE, Jenkins GM, Reinsel GC, Ljung GM (2015) Time series analysis: forecasting and control. John Wiley & Sons, New Jersey
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Ai-driven morphoclimatic regional frequency modelling of sub-daily rainfall-extremes;Journal of Hydrology;2024-03
2. Rainfall forecasting at long lead times for eastern Australia using artificial neural networks;Neural Computing and Applications;2024-01-16
3. A Multilevel Temporal Convolutional Network Model with Wavelet Decomposition and Boruta Selection for Forecasting Monthly Precipitation;Journal of Hydrometeorology;2023-11
4. Enhancing Cyclone Intensity Prediction for Smart Cities Using a Deep-Learning Approach for Accurate Prediction;Atmosphere;2023-10-16
5. Spatiotemporal analysis and predicting rainfall trends in a tropical monsoon-dominated country using MAKESENS and machine learning techniques;Scientific Reports;2023-08-25
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3