Prediction on landslide displacement using a new combination model: a case study of Qinglong landslide in China-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Prediction on landslide displacement using a new combination model: a case study of Qinglong landslide in China

Published:2019-03-21 Issue:3 Volume:96 Page:1121-1139
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Wang Weidong,Li Jiaying,Qu Xia,Han Zheng,Liu Pan

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Natural Science Foundation of Jilin Province

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

http://link.springer.com/content/pdf/10.1007/s11069-019-03595-3.pdf

Reference29 articles.

1. Bui KTT, Bui DT, Zou JG, Doan CV, Revhaug I (2018) A novel hybrid artificial intelligent approach based on neural fuzzy inference model and particle swarm optimization for horizontal displacement modeling of hydropower dam. Neural Comput Appl 29(12):1495–1506. https://doi.org/10.1007/s00521-016-2666-0

2. Cai ZL, Xu WY, Meng YD, Shi C, Wang RB (2016) Prediction of landslide displacement based on GA-LSSVM with multiple factors. Bull Eng Geol Environ 75(2):637–646. https://doi.org/10.1007/s10064-015-0804-z

3. Cao Y, Yin KL, Alexander DE, Zhou C (2016) Using an extreme learning machine to predict the displacement of step-like landslides in relation to controlling factors. Landslides 13(4):725–736. https://doi.org/10.1007/s10346-015-0596-z

4. Chen H, Zeng Z (2011) Deformation prediction of landslide based on genetic-simulated annealing algorithm and BP neural network. In: Proceedings of 4th international workshop on advanced computational intelligence, pp. 675–679. https://doi.org/10.1109/iwaci.2011.6160092

5. Chen W, Pourghasemi HR, Naghibi SA (2017) A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China. Bull Eng Geol Environ 77(2):647–664. https://doi.org/10.1007/s10064-017-1010-y

Cited by 30 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 prediction for landslide with step-like behavior based on stacking ensemble learning strategy;Stochastic Environmental Research and Risk Assessment;2024-07-29

2. Quantification of model uncertainty and variability for landslide displacement prediction based on Monte Carlo simulation;Gondwana Research;2023-11

3. Stability of the Right-Bank Slope of the Oka River;Lecture Notes in Civil Engineering;2023-10-18

4. Secondary-factor division optimization based on ET-GA to improve the accuracy of LSA obtained using SSA-DBN compared to the original division method: a case study in southern Sichuan, China;Bulletin of Engineering Geology and the Environment;2023-07-21

5. Assessment of the distribution and hazard tendency of debris flows along the Chengdu–Changdu section of the Sichuan–Tibet traffic corridor;Bulletin of Engineering Geology and the Environment;2023-06-14

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