Modeling long-term rainfall-runoff time series through wavelet-weighted regularization extreme learning machine
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12145-021-00603-8.pdf
Reference26 articles.
1. Ahmadi M, Moeini A, Ahmadi H, Motamedvaziri B, Zehtabiyan GR (2019) Comparison of the performance of SWAT, IHACRES and artificial neural networks models in rainfall-runoff simulation (case study: Kan watershed, Iran). Phys Chem Earth, Parts A/B/C 111:65–77
2. Azimi H, Bonakdari H, Ebtehaj I (2017) Sensitivity analysis of the factors affecting the discharge capacity of side weirs in trapezoidal channels using extreme learning machines. Flow Meas Instrum 54:216–223
3. Azimi H, Shiri H (2020a) Dimensionless groups of parameters governing the ice-seabed interaction process. J Offshore Mech Arctic Eng 142(5)
4. Azimi H, Shiri H (2020b) Ice-seabed interaction analysis in sand using a gene expression programming-based approach. Appl Ocean Res 98:102120
5. Azimi H, Shiri H (2021) Sensitivity analysis of parameters influencing the ice–seabed interaction in sand by using extreme learning machine. Nat Hazards 105(3):1–29
Cited by 24 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 combined deep CNN-RNN network for rainfall-runoff modelling in Bardha Watershed, India;Artificial Intelligence in Geosciences;2024-12
2. Prediction of precipitation using wavelet-based hybrid models considering the periodicity;Neural Computing and Applications;2024-05-27
3. Simulation of monthly river flow using SVR neural network improved with population-based optimization algorithms;Modeling Earth Systems and Environment;2024-05-13
4. Enhancing short-term streamflow prediction in the Haihe River Basin through integrated machine learning with Lasso;Water Science & Technology;2024-05-01
5. Comparative Evaluation of Deep Learning Techniques in Streamflow Monthly Prediction of the Zarrine River Basin;Water;2024-01-06
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