eprintid: 7032
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/70/32
datestamp: 2023-11-09 16:18:50
lastmod: 2023-11-09 16:18:50
status_changed: 2023-11-09 16:08:18
type: conference_item
metadata_visibility: show
creators_name: Babangida, N.M.
creators_name: Ul Mustafa, M.R.
creators_name: Yusuf, K.W.
creators_name: Isa, M.H.
creators_name: Baig, I.
title: Evaluation of low degree polynomial kernel support vector machines for modelling Pore-water pressure responses
ispublished: pub
keywords: Climate change; Polynomials; Pore pressure; Pressure distribution; Rain; Soft computing; Water, Climatic factors; Coefficient of determination; Field instrumentation; K fold cross validations; Polynomial kernels; Pore-water pressures; Slope management; Unsaturated slopes, Support vector machines
note: cited By 1; Conference of 2016 International Conference on Frontiers of Sensors Technologies, ICFST 2016 ; Conference Date: 12 March 2016 Through 14 March 2016; Conference Code:125630
abstract: Pore-water pressure (PWP) is influenced by climatic changes, especially rainfall. These changes may affect the stability of, particularly unsaturated slopes. Thus monitoring the changes in PWP resulting from climatic factors has become an important part of effective slope management. However, this monitoring requires field instrumentation program, which is resource and labour expensive. Recently, soft computing modelling has become an alternative. Low degree polynomial kernel support vector machine (SVM) was evaluated in modelling the PWP changes. The developed model used pore-water pressure and rainfall data collected from an instrumented slope. Wrapper technique was used to select input features and k-fold cross validation was used to calibrate the model parameters. The developed model showed great promise in modelling the pore-water pressure changes. High correlation, with coefficient of determination of 0.9694 between the predicted and observed changes was obtained. The one degree polynomial SVM model yielded competitive result, and can be used to provide lead time records of PWP which can aid in better slope management. © The Authors.
date: 2016
publisher: EDP Sciences
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009399772&doi=10.1051%2fmatecconf%2f20165904003&partnerID=40&md5=d4c1b087959161802ae9afed69a48cac
id_number: 10.1051/matecconf/20165904003
full_text_status: none
publication: MATEC Web of Conferences
volume: 59
refereed: TRUE
issn: 2261236X
citation:   Babangida, N.M. and Ul Mustafa, M.R. and Yusuf, K.W. and Isa, M.H. and Baig, I.  (2016) Evaluation of low degree polynomial kernel support vector machines for modelling Pore-water pressure responses.  In: UNSPECIFIED.