Correction: Uncertainty Assessment of Surface Water Salinity Using Standalone, Ensemble, and Deep Machine Learning Methods: A Case Study of Lake Urmia

被引:0
|
作者
Bahareh Raheli [1 ]
Nasser Talebbeydokhti [1 ]
Solmaz Saadat [1 ]
Vahid Nourani [2 ]
机构
[1] Shiraz University,Department of Civil and Environmental Engineering
[2] University of Tabriz,Center of Excellence in Hydroinformatics and Faculty of Civil Engineering
[3] World Peace University,undefined
关键词
D O I
10.1007/s40996-024-01666-5
中图分类号
学科分类号
摘要
引用
收藏
页码:4827 / 4827
相关论文
共 50 条
  • [1] Uncertainty Assessment of Surface Water Salinity Using Standalone, Ensemble, and Deep Machine Learning Methods: A Case Study of Lake Urmia
    Raheli, Bahareh
    Talabbeydokhti, Nasser
    Saadat, Solmaz
    Nourani, Vahid
    IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING, 2024, 48 (02) : 1029 - 1047
  • [2] Prediction of Water Level and Salinity of Lakes by Using Artificial Neural Networks, Case Study: Lake Urmia
    Sadeghian, M. S.
    Othman, F.
    Heydari, M.
    Sohrabi, M. S.
    PROCEEDINGS OF THE 35TH IAHR WORLD CONGRESS, VOLS I AND II, 2013, : 2592 - 2599
  • [3] Estimation of soil moisture from remote sensing products using an ensemble machine learning model: a case study of Lake Urmia Basin, Iran
    Seyed Babak Haji Seyed Asadollah
    Ahmad Sharafati
    Mohammad Saeedi
    Shamsuddin Shahid
    Earth Science Informatics, 2024, 17 : 385 - 400
  • [4] Estimation of soil moisture from remote sensing products using an ensemble machine learning model: a case study of Lake Urmia Basin, Iran
    Asadollah, Seyed Babak Haji Seyed
    Sharafati, Ahmad
    Saeedi, Mohammad
    Shahid, Shamsuddin
    EARTH SCIENCE INFORMATICS, 2024, 17 (01) : 385 - 400
  • [5] Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach
    Jalal Shiri
    Shahaboddin Shamshirband
    Ozgur Kisi
    Sepideh Karimi
    Seyyed M Bateni
    Seyed Hossein Hosseini Nezhad
    Arsalan Hashemi
    Water Resources Management, 2016, 30 : 5217 - 5229
  • [6] Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach
    Shiri, Jalal
    Shamshirband, Shahaboddin
    Kisi, Ozgur
    Karimi, Sepideh
    Bateni, Seyyed M.
    Nezhad, Seyed Hossein Hosseini
    Hashemi, Arsalan
    WATER RESOURCES MANAGEMENT, 2016, 30 (14) : 5217 - 5229
  • [7] Modelling lake water's surface changes using environmental and remote sensing data: A case study of lake urmia
    Emami, Hassan
    Zarei, Arastou
    REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2021, 23
  • [8] Correction of Satellite Sea Surface Salinity Products Using Ensemble Learning Method
    Bao, Senliang
    Zhang, Ren
    Wang, Huizan
    Yan, Hengqian
    Chen, Jian
    Wang, Yangjun
    IEEE ACCESS, 2023, 11 : 17870 - 17881
  • [9] Terrestrial water storage anomaly estimating using machine learning techniques and satellite-based data (a case study of Lake Urmia Basin)
    Soltani, Keyvan
    Azari, Arash
    IRRIGATION AND DRAINAGE, 2024, 73 (01) : 215 - 229
  • [10] Detection of Water Surface Using Canny and Otsu Threshold Methods with Machine Learning Algorithms on Google Earth Engine: A Case Study of Lake Van
    Karakus, Pinar
    APPLIED SCIENCES-BASEL, 2025, 15 (06):