A new strategy for prediction of water qualitative and quantitative parameters by deep learning-based models with determination of modelling uncertainties

Author:

Poursaeid Mojtaba12ORCID,Poursaeed Amir Hossein3

Affiliation:

1. Department of Civil Engineering, Payame Noor University, Lorestan, Iran

2. Deputy of Bureau of Technical and Executive, MPO: Plan and Budget Organization, Lorestan, Iran

3. Department of Power Electrical Engineering, Lorestan University, Lorestan, Iran

Publisher

Informa UK Limited

Subject

Water Science and Technology

Reference35 articles.

1. Prediction of water level and water quality using a cnn-lstm combined deep learning approach;Baek S.S.;Water (Switzerland),2020

2. Efficient and data-driven prediction of water breakthrough in subsurface systems using deep long short-term memory machine learning

3. Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model;Barzegar R.;Stochastic Environmental Research and Risk Assessment,2020

4. A novel process monitoring approach based on feature points distance dynamic autoencoder;Cheng F.;Computer Aided Chemical Engineering,2019

5. A VMD-MSMA-LSTM-ARIMA model for precipitation prediction

Cited by 1 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

同舟云学术

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