AI SearchIrregular power consumption identification by using support vector machine and neural network classification (Record no. 65133)
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| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260818144440.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200605s2018 th uu m rtt 0 a eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12307166 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.ET-18-06 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Pradya Panyainkaew |
| 245 10 - TITLE STATEMENT | |
| Title | Irregular power consumption identification by using support vector machine and neural network 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. | 2018 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 59 leaves : |
| Other physical details | ill. (some col.) + |
| Accompanying material | 1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. ET-18-06 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M.Eng.) - Asian Institute of Technology, 2018 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | In this thesis, support vector machine (SVM) is proposed to identify irregular power consumption which can lead to non-technical loss (NTL) in power distribution system, NTL include faulty metering, equipment failure and electrical fraud. The classifier uses customers{u2019} historical power consumption information in 2016 to investigate suspicious instances which cause irregular power consumption behavior. SVM and ANN require training set data of power consumption for classifier development and test set data for evaluation performance. Training set data contains314 irregular power usage instances and 500 regular power consumption instances. Test set data consistsof100 irregular power consumption instances and the other500 regular ones. Moreover, these information are divided into two scenarios, 249 weekdays and 117 weekend/holidays in 2016, respectively. Every instances in both scenarios are represented by individual average power consumption over 96 fifteen-minute interval a day. To represent consumption characteristic as a probability distribution function, Gaussian mixture distribution which is a feature extraction method, is derived from average power consumption. To cluster various power consumption patterns with the same characteristic, k-means clustering method is applied to both the average power consumption over 96 intervals and Gaussian mixture distribution of combined training and test set data. Using training set of data, SVM classifier is developed by creating a linear hyperplane to separate irregular and regular power consumption instances from each other with maximum margin between both regular and irregular power consumption instances boundary. Subsequently, the classifier with a higher than 85% detection rate of each cluster is used to identify irregular power consumption instances in the same cluster of testing set data based on the area under ROC curve (AUC) and accuracy/detection rate criteria. For feature extraction comparison, SVM with Gaussian mixture distribution provides a higher AUC and accuracy than SVM with the average power consumption for both weekday and holidays. To compare with ANN, SVM with Gaussian mixture distribution render a higher accuracy of 92-95% than ANN with both Gaussian mixture distribution (88-92%) and average power consumption (87-91%) for both weekday and weekend/holidays scenarios. SVM with Gaussian mixture distribution is potentially viable to irregular power consumption identification for distribution utilities. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Support vector machines |
| 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 | Energy consumption |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Weerakorn Ongsakul, |
| Relator term | Chairperson |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Singh, Jai Govind, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Than Lin, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Warodom Khamphanchai, |
| Relator term | Examination committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | PEA, |
| Relator term | Scholarship donor |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology Education Cooperation Project, |
| Relator term | Scholarship donor |
| 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. ET-18-06 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B02373">http://203.159.5.9/ait-thesis/detail.php?q=B02373</a> |
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| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
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| Koha item type | 40-Archives |
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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 | Barcode | Date last seen | Copy number | Price effective from | Koha item type | Cost, normal purchase price |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.ET-18-06 | 30050120897144 | 18/08/2026 | 1 | 18/08/2026 | 40-Archives | |||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Thesis no.ET-18-06 | 18/08/2026 | 18/08/2026 | 61-CD-ROM | |||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 18/08/2026 | AIT Thesis no.ET-18-06 | 30050120984181 | 18/08/2026 | 1 | 18/08/2026 | 20-AIT Publication | 50.00 | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 18/08/2026 | AIT Thesis no.ET-18-06 | 30050120984173 | 18/08/2026 | 2 | 18/08/2026 | 20-AIT Publication | 50.00 |