AI SearchEvaluation of AI-based methods for stratigraphic classification (Record no. 40820)
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| fixed length control field | 03703nas a2200397 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260818112658.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260209s20259999th u ms t 000 eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12475142 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.GE-24-10 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Ishara, Petikiri Koralalage Hashan |
| 245 10 - TITLE STATEMENT | |
| Title | Evaluation of AI-based methods for stratigraphic classification |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2025 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 196 leaves : |
| Other physical details | ill.+ |
| Accompanying material | 1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. GE-24-10 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Geotechnical and Earth Resources Engineering |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Eng.) - Asian Institute of Technology, 2025 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Accurate stratigraphic classification is fundamental in geotechnical engineering, as it forms the basis for understanding subsurface conditions and developing safe, reliable, and cost-effective design solutions. However, subsurface soil and rock strata are inherently heterogeneous and spatially variable, while borehole data are typically sparse, incomplete, and noisy. Conventional subsurface modeling and visualization often rely on subjective engineering interpretation, providing limited quantification of uncertainty.This study presents an evaluation of an artificial intelligence (AI)-based method for geotechnical stratigraphy classification, focusing on subsurface profile visualization using machine learning (ML) techniques. A Random Forest (RF) classifier was developed and trained using limited borehole data, incorporating spatial coordinates, elevation, and soil layer thickness to predict lithology classes and generate one-dimensional (1D) and two-dimensional (2D) subsurface profiles. The AI-based predictions were compared with results from conventional kriging and manual interpretation to assess the performance of AI-based modeling in terms of accuracy, stratigraphic consistency, and uncertainty representation.The evaluation results indicate that the RF model outperformed conventional methods, achieving higher classification accuracy and improved consistency between predicted and observed stratigraphy, even with a limited number of boreholes. These findings demonstrate that ML-based approaches, particularly the RF algorithm, provide a robust, data-driven, and objective framework for geotechnical stratigraphic classification.Overall, this study highlights the potential of AI-based methods to enhance the reproducibility and reliability of subsurface modeling, reduce subjectivity in geological interpretation, and enable quantifiable uncertainty estimation offering a practical and efficient alternative for modern geotechnical engineering applications. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Geology, Stratigraphic |
| General subdivision | Classification |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Artificial Intelligence |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chao, Kuo Chieh, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Avirut Puttiwongrak, |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chao, Hsiao-Chou, |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ge, Louis, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SET Dean{u2019}s scholarship, |
| Relator term | Scholarship Donor |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | AIT Scholarship, |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. GE-24-10 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B23578">http://203.159.5.9/ait-thesis/detail.php?q=B23578</a> |
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| a | .b12475142 |
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| a | 260219 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 260219 |
| First date, FD (RLIN) | m |
| -- | h |
| -- | a |
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| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 61-CD-ROM |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : - |
| CREATED | CREATED : 2026-09-02 |
| RECORD Id | RECORD # : i13571631 |
| LPATRON | LPATRON : 0 |
| LCHKIN | LCHKIN : - |
| RENEWALS | # RENEWALS : 0 |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.GE-24-10 | 18/08/2026 | 1 | 18/08/2026 | 61-CD-ROM |