AI SearchApplication of neural network model for daily flood forecasting of inflow and release of Sirikit reservoir and downstream flood discharges (Record no. 6731)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05183nas|a2200433 i 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260817162925.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 030912s2003 th uzm rtt 00| a1eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b11898641 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no. WM-02-12 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Bordin Khanthaprathep |
| 245 10 - TITLE STATEMENT | |
| Title | Application of neural network model for daily flood forecasting of inflow and release of Sirikit reservoir and downstream flood discharges |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Bangkok : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2003 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 70, 45, 3, 2 leaves |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. WM-02-12 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of the Master of Engineering |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M.Eng.) - Asian Institute of Technology, 2003 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | At present, real time operation of Sirikit reservoir in Nan River during flood periods frequently causes severe flooding in downstream areas especially in the vicinity of Uttaradit and Pitsanulok provinces. The excessive release of Sirikit reservoir is due to lacking of information of local inflows from downstream tributaries of Nan river. To forecast flood for real time daily operation and release of the Sirikit reservoir, a flood forecasting model is employed for forecasting daily inflow and release of Sirikit reservoir and daily flood inflows along Nan river downstream of the reservoir. Previous inflow and release of the Sirikit reservoir and flood discharges during large flood years are used in training and testing the model. In this study using Artificial Neural Networks (ANNs, WinNN0.97) is used for forecasting one, three and five days ahead daily inflow of Sirikit reservoir and daily flood discharges along Nan river downstream of Sirikit reservoir at stations N12A(Tha Pla), N27 A (Naresuan dam) and N5A(Phitsanulok). In this study use Back Propagation algorithm and sigmoid transfer function for ANN model. Main streamflow gaging stations and rainfall stations and their observed data were chosen as input data into model. The correlation coefficients between main rainfall stations and streamflow gaging station were determined. The input rainfall and streamflow data for ANN (WinNN0.97) were selected based on highest values of auto and cross-correlation coefficients for training. The parameters of model obtained from training are used in model testing. The accuracy of model is measured by percent of good patterns, the minimum values of Root Mean Square Error (RMSE), Efficiency Index (EI) and also comparison of hydrograph between observed and simulated discharge by ANN model. The models with best performance is selected for sensitivity analysis of model parameters. Each of model is trained and tested for 1 day, 3 days and 5 days ahead flood forecast. The one-day ahead flood forecast has 5 data sets such 1-1, 1-2, 1-3, 1-4 and 1-5. The Three days ahead flood forecast has 3 data sets such 3-1, 3-2 and 3-3. The five days ahead flood forecast have 3 data sets· such 5-1, 5-2 and ·5-3. In this study, there is only one hidden layer and numbers of node in the hidden layer are varied from 1 to 1+2 (I = Number of Input Data). The total cases of one day, three and five days ahead flood forecast in this study are 247 cases. The models with best performance are selected for real time flood forecast. The results show that one day ahead flood forecast are of the best accuracy. The performance of three days ahead flood forecast is better than five days ahead flood forecast. When used ANN model (WinNN0.97) in the real time flood forecasting, the results still good and can be improved by applying a correction factor. Time Delayed Neural Network (TDNN) is used to explore the possibility in flood forecasting at all above-mentioned stations. The accuracy of TDNN models are better than ANN models for the best performance of 1, 3 and 5 days ahead flood forecast. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Neural networks (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Flood forecasting |
| Geographic subdivision | Thailand |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Tawatchai Tingsanchali, |
| Relator term | Chairperson |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Luketina, D.A., |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Clemente, Roberto S., |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Babel, Mukand Singh, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | ASEAN Foundation 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. WM-02-12 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href=" http://203.159.5.9/ait-thesis/detail.php?q=B08511"> http://203.159.5.9/ait-thesis/detail.php?q=B08511</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b11898641 |
| b | mnait |
| c | u |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 240329 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 030912 |
| First date, FD (RLIN) | m |
| -- | a |
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| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnait |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnait |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 20-AIT Publication |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 40-Archives |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : 30050120550958 |
| CREATED | CREATED : 2002-04-15 |
| RECORD Id | RECORD # : i12353292 |
| LPATRON | LPATRON : 1025635 |
| LCHKIN | LCHKIN : 2015-08-02 |
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| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : 30050120550933 |
| CREATED | CREATED : 2002-04-15 |
| RECORD Id | RECORD # : i12353309 |
| LPATRON | LPATRON : 1028328 |
| LCHKIN | LCHKIN : 2018-05-27 |
| RENEWALS | # RENEWALS : 0 |
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| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : 30050120236020 |
| CREATED | CREATED : 2016-03-25 |
| RECORD Id | RECORD # : i1290949x |
| 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 | Cost, normal purchase price | Total checkouts | Full call number | Barcode | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | 50.00 | AIT Thesis no. WM-02-12 | 30050120550958 | 17/08/2026 | 1 | 17/08/2026 | 20-AIT Publication | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | 50.00 | AIT Thesis no. WM-02-12 | 30050120550933 | 17/08/2026 | 2 | 17/08/2026 | 20-AIT Publication | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no. WM-02-12 | 30050120236020 | 17/08/2026 | 17/08/2026 | 40-Archives |