Improved Permeability Prediction of Porous Media by Feature Selection and Machine Learning Methods Comparison-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Improved Permeability Prediction of Porous Media by Feature Selection and Machine Learning Methods Comparison

Published:2022-03 Issue:2 Volume:36 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Tian J. W.¹,Qi Chongchong²^ORCID,Peng Kang³,Sun Yingfeng⁴,Mundher Yaseen Zaher⁵

Affiliation:

1. School of Resources and Safety Engineering, Central South Univ., Changsha 410083, China.

2. Professor, School of Resources and Safety Engineering, Central South Univ., Changsha 410083, China. ORCID:

3. Professor, School of Resources and Safety Engineering, Central South Univ., Changsha 410083, China (corresponding author).

4. School of Civil and Resource Engineering, Univ. of Science and Technology Beijing, Beijing 100083, China.

5. Sustainable Developments in Civil Engineering Research Group, Faculty of Civil engineering, Ton Duc Thang Univ., Ho Chi Minh City 700000, Vietnam.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000983

Reference90 articles.

1. A hybrid particle swarm optimization and support vector regression model for modelling permeability prediction of hydrocarbon reservoir

2. Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks

3. Enhanced geothermal system modelling with multiple pore media: Thermo-hydraulic coupled processes

4. Permeability prediction and diagenesis in tight carbonates using machine learning techniques

5. Influence of pore structure parameters on flow characteristics based on a digital rock and the pore network model

Cited by 14 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. An improved convolutional neural network for predicting porous media permeability from rock thin sections;Gas Science and Engineering;2024-07

2. A developed convolutional neural network model for accurately and stably predicting effective thermal conductivity of gradient porous ceramic materials;International Journal of Heat and Mass Transfer;2024-06

3. Real-Time Prediction of Petrophysical Properties Using Machine Learning Based on Drilling Parameters;ACS Omega;2024-04-08

4. Swin transformer based transfer learning model for predicting porous media permeability from 2D images;Computers and Geotechnics;2024-04

5. An accelerated lattice Boltzmann method for natural convection coupled with convolutional neural network;Physics of Fluids;2024-02-01

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