AI SearchEvaluation of factors influencing soil-water infiltration behavior using machine learning approach (Record no. 40963)
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| fixed length control field | 03449nas a2200361 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260818112726.0 |
| 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 | .b1247504x |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.GE-24-01 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Napattarapong Kaenpuek |
| 245 10 - TITLE STATEMENT | |
| Title | Evaluation of factors influencing soil-water infiltration behavior using machine learning approach |
| 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 | 164 leaves : |
| Other physical details | ill.+ |
| Accompanying material | 1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. GE-24-01 |
| 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. | Landslides pose significant threats to lives, infrastructure, and the environment, often triggered by rainfall-induced soil infiltration that reduces slope stability. Accurate prediction of soil-water infiltration under varying rainfall and slopeconditions is crucial for landslide risk mitigation. Traditional deterministic models, while physically rigorous, require detailed input parameters that are difficult to obtain in practice, whereas purely data-driven approaches may lack physical consistency. This study develops and evaluates a Physics-Informed Neural Network (PINN) framework that integrates the governing Richards{u2019} equation with observational data to predict soil moisture profiles in unsaturated slopes subjected to rainfall. Laboratory experiments were conducted using a physical slope model filled with red clayey sand and white sandy clay under controlled rainfall intensities (10, 50, and 90{u202F}mm/h) and slope angles (0°, 15°, and 30°). Soil properties, including soil-water characteristic curves, were determined experimentally, and Finite Element Method (FEM) simulations were calibrated against observed data. The PINN was first trained using observational data only and then extended to a hybrid strategy combining FEM and observations. Results show that the observation-only PINN captured the general infiltration trend but produced smoother, less accurate wetting fronts, particularly at greater depths. In contrast, the hybrid-trained PINN improved accuracy, capturing infiltration dynamics and wetting front propagation more effectively, with lower error metrics and better alignment with observations and FEM results. These findings indicate that, with denser sensor networks in the future, PINNs trained on richer observational data could further enhance prediction performance, supporting real-time landslide hazard assessment. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Landslide hazard analysis |
| General subdivision | Data processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Soil science |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning |
| 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 |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Royal Thai Government Fellowship, |
| 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-24-01 |
| 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=B23569">http://203.159.5.9/ait-thesis/detail.php?q=B23569</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b1247504x |
| b | mnarc |
| c | a |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 260219 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 260218 |
| 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 # : i13571539 |
| LPATRON | LPATRON : 0 |
| LCHKIN | LCHKIN : - |
| RENEWALS | # RENEWALS : 0 |
| -- | # OVERDUE : 0 |
| -- | IUSE3 : 0 |
| -- | TOT CHKOUT : 0 |
| -- | TOT RENEW : 0 |
| 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-24-01 | 18/08/2026 | 1 | 18/08/2026 | 61-CD-ROM |