A Comparative Assessment of Models to Predict Monthly Rainfall in Australia
Author:
Funder
Australian Research Council
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
http://link.springer.com/article/10.1007/s11269-018-1903-y/fulltext.html
Reference32 articles.
1. Australian weather and seasons (2013) http://www.australia.gov.au/about-australia/australian-story/austn-weather-and-the-seasons
2. Abbot J, Marohasy J (2012) Application of artificial neural networks to rainfall forecasting in Queensland, Australia. Adv Atmos Sci 29(4):717–730
3. Abbot J, Marohasy J (2014) Input selection and optimisation for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks. Atmos Res 138:166–178
4. Aksoy H, Dahamsheh A (2009) Artificial neural network models for forecasting monthly precipitation in Jordan. Stochastic Environ Res Risk Assess 23:917–931
5. Al-Qahtani F, Crone S (2013) Multivariate k-nearest neighbour regression for time series data - A novel algorithm for forecasting UK electricity demand. In: The 2013 international joint conference on neural networks (IJCNN), pp 1–8
Cited by 25 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. A Indian Rainfall Prediction Using Machine Learning Algorithms: A Comparative Study;2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT);2024-07-04
2. From Data to Forecast: A Comparative Evaluation of Machine Learning and Deep Learning Models for Rainfall Prediction in Australia;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02
3. Data-driven multi-step prediction and analysis of monthly rainfall using explainable deep learning;Expert Systems with Applications;2024-01
4. A Multilevel Temporal Convolutional Network Model with Wavelet Decomposition and Boruta Selection for Forecasting Monthly Precipitation;Journal of Hydrometeorology;2023-11
5. Evaluation of a novel hybrid lion swarm optimization – AdaBoostRegressor model for forecasting monthly precipitation;Sustainable Computing: Informatics and Systems;2023-09
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