A review of artificial intelligence methods for predicting gravity dam seepage, challenges and way-out
Author:
Affiliation:
1. a Department of Civil Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, India
2. b Department of Chemical Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, India
Abstract
Publisher
IWA Publishing
Subject
Management, Monitoring, Policy and Law,Pollution,Water Science and Technology,Ecology,Civil and Structural Engineering,Environmental Engineering
Link
https://iwaponline.com/aqua/article-pdf/72/7/1228/1262725/jws0721228.pdf
Reference101 articles.
1. Multi-parametric modeling of water treatment plant using AI-based non-linear ensemble
2. Investigation and Estimation of Seepage Discharge Through Homogenous Earth Dam with Core by Using SEEP/W Model and Artificial Neural Network
3. Performance evaluation of a genetic algorithm-based linked simulation-optimization model for optimal hydraulic seepage-related design of concrete gravity dams
4. Statistical modeling of monthly streamflow using time series and artificial neural network models: Hindiya Barrage as a case study
5. Vehicle Price Classification and Prediction Using Machine Learning in the IoT Smart Manufacturing Era
Cited by 5 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. Displacement observation data-based structural health monitoring of concrete dams: A state-of-art review;Structures;2024-10
2. A review of artificial intelligence in dam engineering;Journal of Infrastructure Intelligence and Resilience;2024-09
3. Optimal design of diversion dams based on Upgraded Multi-Objective Particle Swarm Optimization (UMOPSO);International Journal of Construction Management;2024-07-11
4. Monitoring model group of seepage behavior of earth-rock dam based on the mutual information and support vector machine algorithms;Structural Health Monitoring;2024-03-28
5. A Dam Safety State Prediction and Analysis Method Based on EMD-SSA-LSTM;Water;2024-01-24
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