Convolutional Neural Network -Support Vector Machine Model-Gaussian Process Regression: A New Machine Model for Predicting Monthly and Daily Rainfall
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/s11269-023-03519-8.pdf
Reference34 articles.
1. Abbot J, Marohasy J (2014) Input selection and optimisation for monthly rainfall forecasting in queensland, australia, using artificial neural networks. Atmos Res. https://doi.org/10.1016/j.atmosres.2013.11.002
2. Abedinia O, Amjady N, Ghasemi A (2016) A new metaheuristic algorithm based on shark smell optimization. Complexity 21(5):97–116
3. Adaryani FR, Mousavi SJ, Jafari F (2022) Short-term rainfall forecasting using machine learning-based approaches of PSO-SVR, LSTM and CNN. J Hydrol 614:128463
4. Afshari Nia M, Panahi F, Ehteram M (2023) Convolutional neural network-ANN-E (Tanh): A new deep learning model for predicting rainfall. Water Resour Manag 1–26
5. Aswin S, Geetha P, Vinayakumar R (2018) Deep learning models for the prediction of rainfall. Int Conf Commun Signal Process (ICCSP). IEEE
Cited by 14 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. Advanced Forecasting of Drought Zones in Canada Using Deep Learning and CMIP6 Projections;Climate;2024-08-10
2. Statistical Downscaling of Remote Sensing Precipitation Estimates Using MODIS Cloud Properties Data over Northeastern Greece;Remote Sensing in Earth Systems Sciences;2024-06
3. An evaluation of statistical and deep learning-based correction of monthly precipitation over the Yangtze River basin in China based on CMIP6 GCMs;Environment, Development and Sustainability;2024-05-10
4. Prediction of key quality attributes in Salvia miltiorrhiza standard decoction using a Gaussian process regression model;Phytochemical Analysis;2024-04-30
5. Read-First LSTM model: A new variant of long short term memory neural network for predicting solar radiation data;Energy Conversion and Management;2024-04
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