Predicting Geotechnical Investigation Using the Knowledge Based System
Joint Authors
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-05
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The purpose of this paper is to evaluate the optimal number of investigation points and each field test and laboratory test for a proper description of a building site.
These optimal numbers are defined based on their minimum and maximum number and with the equivalent investigation ratio.
The total increments of minimum and maximum number of investigation points for different building site conditions were determined.
To facilitate the decision-making process for a number of investigation points, an Adaptive Network Fuzzy Inference System (ANFIS) was proposed.
The obtained fuzzy inference system considers the influence of several entry parameters and computes the equivalent investigation ratio.
The developed model (ANFIS-SI) can be applied to characterize any building site.
The ANFIS-SI model takes into account project factors which are evaluated with a rating from 1 to 10.
The model ANFIS-SI, with integrated recommendations can be used as a systematic decision support tool for engineers to evaluate the number of investigation points, field tests, and laboratory tests for a proper description of a building site.
The determination of the optimal number of investigative points and the optimal number of each field test and laboratory test is presented on reference case.
American Psychological Association (APA)
Žlender, Bojan& Jelušič, Primož. 2016. Predicting Geotechnical Investigation Using the Knowledge Based System. Advances in Fuzzy Systems،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1095039
Modern Language Association (MLA)
Žlender, Bojan& Jelušič, Primož. Predicting Geotechnical Investigation Using the Knowledge Based System. Advances in Fuzzy Systems No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1095039
American Medical Association (AMA)
Žlender, Bojan& Jelušič, Primož. Predicting Geotechnical Investigation Using the Knowledge Based System. Advances in Fuzzy Systems. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1095039
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1095039