Predicting Geotechnical Investigation Using the Knowledge Based System
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...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2016/4867498 |
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| _version_ | 1832548109570277376 |
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| author | Bojan Žlender Primož Jelušič |
| author_facet | Bojan Žlender Primož Jelušič |
| author_sort | Bojan Žlender |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-38336f9bb4594f2383b80452bc536a6c |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-38336f9bb4594f2383b80452bc536a6c2025-02-03T06:42:12ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2016-01-01201610.1155/2016/48674984867498Predicting Geotechnical Investigation Using the Knowledge Based SystemBojan Žlender0Primož Jelušič1Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Smetanova 17, SI-2000 Maribor, SloveniaFaculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Smetanova 17, SI-2000 Maribor, SloveniaThe 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.http://dx.doi.org/10.1155/2016/4867498 |
| spellingShingle | Bojan Žlender Primož Jelušič Predicting Geotechnical Investigation Using the Knowledge Based System Advances in Fuzzy Systems |
| title | Predicting Geotechnical Investigation Using the Knowledge Based System |
| title_full | Predicting Geotechnical Investigation Using the Knowledge Based System |
| title_fullStr | Predicting Geotechnical Investigation Using the Knowledge Based System |
| title_full_unstemmed | Predicting Geotechnical Investigation Using the Knowledge Based System |
| title_short | Predicting Geotechnical Investigation Using the Knowledge Based System |
| title_sort | predicting geotechnical investigation using the knowledge based system |
| url | http://dx.doi.org/10.1155/2016/4867498 |
| work_keys_str_mv | AT bojanzlender predictinggeotechnicalinvestigationusingtheknowledgebasedsystem AT primozjelusic predictinggeotechnicalinvestigationusingtheknowledgebasedsystem |