AI SearchApplying decision trees, artificial neural networks and support vector machine to classify the potential of gas stations (Record no. 7337)
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 170110s2012 th uu|m rtt 0| a1eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12177635 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT RSPR no.IM-12-07 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Tanawat Sermvongtrakul |
| 245 10 - TITLE STATEMENT | |
| Title | Applying decision trees, artificial neural networks and support vector machine to classify the potential of gas stations |
| 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. | 2012 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 54 p. : |
| Other physical details | ill. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Research studies project report ; |
| Volume/sequential designation | no. IM-12-07 |
| 500 ## - GENERAL NOTE | |
| General note | A research study submitted in partial fulfillment of the requirements forthedegree of Master of Science inInformation Management, School of Engineering of Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Research Studies Project Report (M.Sc.) - Asian Institute of Technology, 2012 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | In oil retail industries, gas stations are builtto serve households and industries. An operation of a gas station has a very high risk of loss. To reduce thatrisk, managements need to consider several factors influencing revenues of the station before building a new gas station.With the rapid development in information technology, many different data mining approaches are applied to support management{u2019}s decisions. This study focuses on using several data mining techniques to classify the potential of gas stations. The potential means the capability of growth or being without loss; therefore, this study uses sales volume as an indicator of the potential of gas stations. Using classification techniques in the data mining candiscover some hidden knowledge on existing gas station data and other related information and the knowledgecan also be used for helping the management making a decision for building the new station,which is very beneficial.This study conducted 3 experiments, which use artificial neural networks, support vector machine and decision trees. The results show that using artificial neural networks hasthe highest accuracy in classifying the potential of gas stations. It is more than 85% accuracy for all models. On the contrary, using support vector machine and decision trees, both of them getloweraccuracy rate on testing data. Based on these results,the artificial neural networks technique can serve as a decision support tool for classify a potential of a new gas station, which can reduce the human error in the decision-making process or even help to the management to make a decision with very high accuracy. |
| 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 | Decision trees |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Decision support systems |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Data mining |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Guha, Sumanta, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Vatcharaporn Esichaikul, |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Duboz, Raphael, |
| 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 | Research studies project report ; |
| Volume/sequential designation | no. IM-12-07 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B01437">http://203.159.5.9/ait-thesis/detail.php?q=B01437</a> |
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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 RSPR no.IM-12-07 | 30050120409759 | 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 RSPR no.IM-12-07 | 30050120409742 | 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 RSPR no.IM-12-07 | 30050120403687 | 17/08/2026 | 1 | 17/08/2026 | 40-Archives |