NDLI: Intelligent prediction of settlement ratio for soft clay with stone columns using embankment improvement techniques

Content Provider	Springer Nature Link
Author	Chik, Zamri Aljanabi, Qasim A.
Copyright Year	2013
Abstract	Construction of highway roads, railways and other engineering structures on soft clay soils normally encounters problems related to excessive settlement issues. The conventional methods are inadequate to analyze and to predict the settlement behavior. Artificial neural network systems are included to predict settlement under embankment load using soft soil properties together with various geometric parameters as inputs for each stone column arrangement and embankment conditions. A case study site investigated field data are taken from a highway project Lebuhraya Pantai Timur2 in Terengganu, Malaysia. Actual angle of internal friction (ϕ), spacing ratio (s/D), cylindrical ratio (L/D) and height of the embankment (H) were used as the input parameters, while the settlement ratio was the main output. The properties of materials on a stone column (ϕ) have high relative importance (40.15 %) compared with the other parameters. Two techniques namely non-cross-validation (β NCV) and ten-fold cross-validation (β FCV) were used to build the ANN model. The β FCV model gives higher efficiency of 0.985 for training and 0.939 for testing, while β NCV model gives 0.937 and 0.905. The β FCV model provides results of greater accuracy as compared to the β NCV models.
Starting Page	73
Ending Page	82
Page Count	10
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	25
Issue Number	1
e-ISSN	14333058
Language	English
Publisher	Springer London
Publisher Date	2013-07-13
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial neural network Settlement ratio Soil improvement Stone column technique Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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