Control of ground settlements caused by EPBS tunneling using an intelligent predictive model (Record no. 8569)

000 -LEADER
fixed length control field a
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190319155434.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190319b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 8151
Author Moeinossadat, Sayed Rahim
245 ## - TITLE STATEMENT
Title Control of ground settlements caused by EPBS tunneling using an intelligent predictive model
250 ## - EDITION STATEMENT
Volume, Issue number Vol. 48(3), September
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York
Name of publisher, distributor, etc. Springer
Year 2018
300 ## - PHYSICAL DESCRIPTION
Pagination 420-429p.
520 ## - SUMMARY, ETC.
Summary, etc. This paper deals with the control of ground surface settlement due to excavation of shallow tunnels. In order to control the settlement, one should be able to predict it, based on the prediction one may consider required preventions and protections. Prediction of surface settlement depends on several parameters and each parameter has an effect on the other. Application of the traditional methods could become impractical as the proposed equations might have low accuracy. To overcome these limitations, intelligent methods could be implemented. The present study aims to develop an intelligent model for prediction of the surface settlement in Shanghai subway line 2 project using adaptive neuro-fuzzy inference system (ANFIS). The results indicated that the proposed model had an appropriate performance. In order to perform sensitivity analysis of the ANFIS model, cosine amplitude method (CAM) was used and according to the results it was found that the operational, geometric and strength parameters had the highest impacts, respectively. Furthermore, amongst the input parameters, the two parameters of grout filling percentage (n) and grouting pressure (P) were identified as the most effective ones. The values of critical settlement were determined based on Rankin’s criteria of damage risk assessment to control the ground settlement. Then, the corresponding surface settlement was minimized by changing values of the input parameters. According to the results, control of machine operational factors particularly the n and P parameters had a crucial role in reducing surface settlement and preventing pertinent damages.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 4621
Topical term or geographic name entry element Civil Engineering
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 8152
Co-Author Ahangari, Kaveh
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 8153
Co-Author Shahriar, Kourosh
773 0# - HOST ITEM ENTRY
International Standard Serial Number 0971-9555
Place, publisher, and date of publication Switzerland Springer
Title Indian geotechnical journal
856 ## - ELECTRONIC LOCATION AND ACCESS
URL https://link.springer.com/article/10.1007/s40098-017-0253-7
Link text Click here
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Articles Abstract Database
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Barcode Date last seen Price effective from Koha item type
          School of Engineering & Technology School of Engineering & Technology Archieval Section 2019-03-29 2018241 2019-06-10 2019-03-29 Articles Abstract Database
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