Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach

被引：0
|
作者：
Rana Muhammad Adnan
Andrea Petroselli
Salim Heddam
Celso Augusto Guimarães Santos
Ozgur Kisi
机构：
[1] Hohai University,State Key Laboratory of Hydrology
[2] University of Tuscia,Water Resources and Hydraulic Engineering
[3] Faculty of Science,Department of Economy, Engineering, Society and Business (DEIM)
[4] Agronomy Department,Department of Civil and Environmental Engineering
[5] Hydraulics Division,Civil Engineering Department
[6] Federal University of Paraíba,Institute of Research and Development
[7] Ilia State University,undefined
[8] Duy Tan University,undefined
来源：
Natural Hazards | 2021年 / 105卷
关键词：
Machine learning; Physically event-based conceptual method; EBA4SUB; Hourly rainfall–runoff modeling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：2987 / 3011
页数：24
相关论文
共 50 条
  • [31] A Machine Learning Approach to Modeling Satellite Behavior
    Mital, Rohit
    Cates, Kim
    Coughlin, Joseph
    Ganji, Geetha
    2019 IEEE INTERNATIONAL CONFERENCE ON SPACE MISSION CHALLENGES FOR INFORMATION TECHNOLOGY (SMC-IT 2019), 2019, : 62 - 69
  • [32] Modeling machine learning: A cognitive economic approach ☆
    Caplin, Andrew
    Martin, Daniel
    Marx, Philip
    JOURNAL OF ECONOMIC THEORY, 2025, 224
  • [33] Different Time-Increment Rainfall Prediction Models: a Machine Learning Approach Using Various Input Scenarios
    Rahimi, Anas
    Yashooa, Noor Kh.
    Ahmed, Ali Najah
    Sherif, Mohsen
    El-shafie, Ahmed
    WATER RESOURCES MANAGEMENT, 2024, : 1677 - 1696
  • [34] A Comparison of Machine Learning Models for Predicting Rainfall in Urban Metropolitan Cities
    Kumar, Vijendra
    Kedam, Naresh
    Sharma, Kul Vaibhav
    Khedher, Khaled Mohamed
    Alluqmani, Ayed Eid
    SUSTAINABILITY, 2023, 15 (18)
  • [35] A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff
    Aieb, Amir
    Liotta, Antonio
    Kadri, Ismahen
    Madani, Khodir
    SENSORS, 2022, 22 (09)
  • [36] Radiologist vs Machine Learning: A Comparison of Performance in Cancer Imaging
    Provenzano, Destie
    Rao, Yuan James
    Goyal, Sharad
    Haji-Momenian, Shawn
    Lichtenberger, John
    Loew, Murray
    2021 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP (AIPR), 2021,
  • [37] A Comparison of Deep Learning vs Traditional Machine Learning for Electricity Price Forecasting
    O'Leary, Christian
    Lynch, Conor
    Bain, Rose
    Smith, Gary
    Grimes, Diarmuid
    2021 4TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMPUTER TECHNOLOGIES (ICICT 2021), 2021, : 6 - 12
  • [38] Learning Orthodontic Cephalometry through Augmented Reality: A Conceptual Machine Learning Validation Approach
    Rao, Gururajaprasad Kaggal Lakshmana
    Mokhtar, Norehan
    Iskandar, Yulita Hanum P.
    Srinivasa, Arvind Channarayapatna
    2018 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICELTICS): INTELLIGENT DEVICES AND COMPUTING FOR ACCELERATING INDUSTRY 4.0 AND ENRICHING SMART SOCIETIES, 2018, : 133 - 138
  • [39] Predicting flood stages in watersheds with different scales using hourly rainfall dataset: A high-volume rainfall features empowered machine learning approach
    Qiao, Lei
    Livsey, Daniel
    Wise, Jarrett
    Kadavy, Kem
    Hunt, Sherry
    Wagner, Kevin
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 950
  • [40] Machine learning for compositional disorder: A comparison between different and machine frameworks
    Yaghoobi, Mostafa
    Alaei, Mojtaba
    COMPUTATIONAL MATERIALS SCIENCE, 2022, 207
12345