SWS Academic Research eLibraryEarth & Planetary Sciences

Scholarly record

PERFORMANCE OF FUZZY LOGIC IN DETERMINATION OF UNSTABLE POINTS IN LEVELING NETWORKS

C. T. Celik

First published: 2010DOI pendingView metrics

Abstract

A man-made structure or natural phenomena like crustal movement, vertical land movements, subsidence determination, etc. is subject to deformations due to forces on them. Deformations of a structure require rigorous analysis to reflect significant movements. In general, deformation analysis relies on the reference network that is set outside the deforming area so that a comparison could be possible. However, a geodetic reference network is itself subject to movement. Therefore, the stability of the reference network needs to be conformed by some suitable methods. There exist a number of methods for performing the determination of stable and unstable points in the reference network. In this study, based on the fuzzy logic algorithm, a new method of detecting stable and unstable points in a reference network designed for detection of vertical movements is recommended. To test the proposed method a simulation was carried out and the results were presented.

Publication details

Title
PERFORMANCE OF FUZZY LOGIC IN DETERMINATION OF UNSTABLE POINTS IN LEVELING NETWORKS
Authors
C. T. Celik
Proceedings
10th International Multidisciplinary Scientific GeoConference SGEM2010
Publisher
SGEM Scientific GeoConference
Year
2010
Pages
917-926
SWS Citekey
Celik2010311
ISSN
1314-2704
ISBN
954-91818-1-2
Language
en
Publication type
Conference Paper
Keywords
References9
  1. Caspary W. F. Concepts of Network and Deformation Analysis. School of Surveying Monograph 11, 1987

  2. Hekimoglu S.,. Robustifying Conventional Outlier Detection Procedure. J. Surv. Eng., Vol. 125, No. 2, May, 1999.

  3. Kennie T. J. and Petrie G., Engineering Surveying Technology. London, 1993.

  4. Chrzanowski A. and Chen YQ., Report of ad-hoc committee on the analysis of deformation surveys. 18* FIG Int. Congr. Toronto 19, 1986.

  5. Cross P A., Advanced Least Square Applied to Position-Fixing. School of Surveying University of East London, Working Paper no. 6, London, 1 994.

  6. L. A. Zadeh, L. A. Fuzzy sets, Information and Control, vol. 8, no. 3, June, pp. 338353, 1965

  7. Jang, J. S. R. ANFIS: adaptive-network-based fuzzy inference systems. IEEE Transactions on System, Man and Cybernetics, 23 (3), 665-685, 1993.

  8. Fuzzy Logic Toolbox.. User guide version2, the Mathworks inc. 2002

  9. Kim, J. and N. Kasabov. HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems. Neural Networks 12, 1301-13 19pp, 1999.

View or Download full articleAccess options
Full paper accessChoose SWS login, librarian support, or instant article download.

SWS access login

Login as SWS Scientific Committee

Authors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.

For librarian assistance: [email protected]

Purchase Instant Access

48-hour online accessComing soon
Online-only accessComing soon
Download the full article in PDF formatEUR 35
  • Article can be downloaded after successful payment.
  • Article may be used according to SWS library access terms.
  • Article cannot be redistributed.
Get full paper

Back to publication list