Predicting Geotechnical Investigation Using the Knowledge Based System

Joint Authors

Žlender, Bojan
Jelušič, Primož

Source

Advances in Fuzzy Systems

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

Mathematics

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