Erratum to: An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland

被引：0
|
作者：
Ravinesh C. Deo
Mehmet Şahin
机构：
[1] University of Southern Queensland,School of Agricultural Computational and Environmental Sciences, International Centre of Applied Climate Science (ICACS)
[2] Siirt University,Department of Electrical and Electronics Engineering
来源：
Environmental Monitoring and Assessment | 2016年 / 188卷
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [31] Forecasting Model of Coal Mine Water Inrush Based on Extreme Learning Machine
    Zhao, Zuopeng
    Li, Pei
    Xu, Xinzheng
    APPLIED MATHEMATICS & INFORMATION SCIENCES, 2013, 7 (03): : 1243 - 1250
  • [32] A Hybrid Model for Monthly Precipitation Time Series Forecasting Based on Variational Mode Decomposition with Extreme Learning Machine
    Li, Guohui
    Ma, Xiao
    Yang, Hong
    INFORMATION, 2018, 9 (07)
  • [33] Statistical downscaling of global climate model outputs to monthly precipitation via extreme learning machine: A case study
    Alizamir, Meysam
    Moghadam, Mehdi Azhdary
    Monfared, Arman Hashemi
    Shamsipour, Aliakbar
    ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, 2018, 37 (05) : 1853 - 1862
  • [34] Machine learning methods for empirical streamflow simulation: a comparison of model accuracy, interpretability, and uncertainty in seasonal watersheds
    Shortridge, Julie E.
    Guikema, Seth D.
    Zaitchik, Benjamin F.
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2016, 20 (07) : 2611 - 2628
  • [35] Reservoir water balance simulation model utilizing machine learning algorithm
    Latif, Sarmad Dashti
    Ahmed, Ali Najah
    Sherif, Mohsen
    Sefelnasr, Ahmed
    El-Shafie, Ahmed
    ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (01) : 1365 - 1378
  • [36] Variations in the mean, seasonal and extreme water level on the Latvian coast, the eastern Baltic Sea, during 1961-2018
    Mannikus, Rain
    Soomere, Tarmo
    Viska, Maija
    ESTUARINE COASTAL AND SHELF SCIENCE, 2020, 245
  • [37] A hybrid groundwater level prediction model using signal decomposition and optimised extreme learning machine
    Seidu, Jamel
    Ewusi, Anthony
    Kuma, Jerry Samuel Yaw
    Ziggah, Yao Yevenyo
    Voigt, Hans-Jurgen
    MODELING EARTH SYSTEMS AND ENVIRONMENT, 2022, 8 (03) : 3607 - 3624
  • [38] A hybrid groundwater level prediction model using signal decomposition and optimised extreme learning machine
    Jamel Seidu
    Anthony Ewusi
    Jerry Samuel Yaw Kuma
    Yao Yevenyo Ziggah
    Hans-Jurgen Voigt
    Modeling Earth Systems and Environment, 2022, 8 : 3607 - 3624
  • [39] A Novel Approach for Prediction of Monthly Ground Water Level Using a Hybrid Wavelet and Non-Tuned Self-Adaptive Machine Learning Model
    Maryam Malekzadeh
    Saeid Kardar
    Keivan Saeb
    Saeid Shabanlou
    Lobat Taghavi
    Water Resources Management, 2019, 33 : 1609 - 1628
  • [40] A Novel Approach for Prediction of Monthly Ground Water Level Using a Hybrid Wavelet and Non-Tuned Self-Adaptive Machine Learning Model
    Malekzadeh, Maryam
    Kardar, Saeid
    Saeb, Keivan
    Shabanlou, Saeid
    Taghavi, Lobat
    WATER RESOURCES MANAGEMENT, 2019, 33 (04) : 1609 - 1628
12345