Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91052
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Civil and Environmental Engineering | en_US |
dc.creator | Elbaz, K | en_US |
dc.creator | Shen, SL | en_US |
dc.creator | Zhou, AN | en_US |
dc.creator | Yin, ZY | en_US |
dc.creator | Lyu, HM | en_US |
dc.date.accessioned | 2021-09-09T03:39:16Z | - |
dc.date.available | 2021-09-09T03:39:16Z | - |
dc.identifier.issn | 2352-3409 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/91052 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2020 The Author(s). Published by Elsevier Inc. | en_US |
dc.rights | This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) | en_US |
dc.rights | The following publication Khalid Elbaz, Shui-Long Shen, Annan Zhou, Zhen-Yu Yin, Hai-Min Lyu, Data in intelligent approach for estimation of disc cutter life using hybrid metaheuristic algorithm, Data in Brief, Volume 33, 2020, 106479 is available at https://doi.org/10.1016/j.dib.2020.106479. | en_US |
dc.subject | Disc cutter | en_US |
dc.subject | GMDH-type neural network | en_US |
dc.subject | Tunnel boring machine | en_US |
dc.subject | Genetic algorithm | en_US |
dc.title | Data in intelligent approach for estimation of disc cutter life using hybrid metaheuristic algorithm | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 33 | en_US |
dc.identifier.doi | 10.1016/j.dib.2020.106479 | en_US |
dcterms.abstract | This data in brief presents the monitoring data measured during shield tunnelling of Guangzhou-Shenzhen intercity railway project. The monitoring data includes shield operational parameters, geological conditions, and geometry at the site. The presented data were arbitrarily split into two subsets including the training and testing datasets. The field observations are compared to the forecasting values of the disc cutter life assessed using a hybrid metaheuristic algorithm proposed for "Prediction of disc cutter life during shield tunnelling with artificial intelligent via incorporation of genetic algorithm into GMDH-type neural network"[1]. The presented data can provide a guidance for cutter exchange in shield tunnelling. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Data in brief, Dec. 2020, v. 33, 106479 | en_US |
dcterms.isPartOf | Data in brief | en_US |
dcterms.issued | 2020-12 | - |
dc.identifier.isi | WOS:000600652300145 | - |
dc.identifier.pmid | 33241094 | - |
dc.identifier.artn | 106479 | en_US |
dc.description.validate | 202109 bchy | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | - |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
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Yin_Data_intelligent_approach.pdf | 982.98 kB | Adobe PDF | View/Open |
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