Simulation of groundwater level using MODFLOW, extreme learning machine and Wavelet-Extreme Learning Machine models-Reference-Cited by-同舟云学术

Simulation of groundwater level using MODFLOW, extreme learning machine and Wavelet-Extreme Learning Machine models

Published:2019-10 Issue: Volume:9 Page:100279
ISSN:2352-801X
Container-title:Groundwater for Sustainable Development
language:en
Short-container-title:Groundwater for Sustainable Development

Author:

Malekzadeh Maryam,Kardar Saeid,Shabanlou Saeid

Publisher

Elsevier BV

Subject

Water Science and Technology,Geography, Planning and Development,Environmental Chemistry,Environmental Engineering

Reference25 articles.

1. Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models;Barzegar;Sci. Total Environ.,2017

2. Characterizing an unknown pollution source in groundwater resources systems using PSVM and PNN;Bashi-Azghadi;Expert Syst. Appl.,2010

3. Reduced order modeling of the Newton formulation of MODFLOW to solve unconfined groundwater flow;Boyce;Adv. Water Resour.,2015

4. An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model;Chen;J. Hydrol.,2017

5. Comparative analysis of different boundary conditions and their influence on numerical hydrogeological modeling of Palmital watershed, southeast Brazil;Coelho;J. Hydrol.: Reg. Stud.,2017

Cited by 66 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. Development of a coupled surface water–groundwater model for the spatiotemporal simulation of river–aquifer interactions;Irrigation and Drainage;2024-07-21

2. Long-term effects of subsurface structures on groundwater level in a typical urban area of Shanghai, China;Hydrogeology Journal;2024-05-25

3. Hybrid machine learning models for groundwater level prediction in a snow‐dominated region: An evaluation of EEMD, VMD and EWT decomposition techniques;Hydrological Processes;2024-05

4. Optimal operation of the dam reservoir in real time based on generalized structure of group method of data handling and optimization technique;Applied Water Science;2024-04-25

5. Evolution of high-filling loess slope under long-term seasonal fluctuation of groundwater;CATENA;2024-04