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Pregled bibliografske jedinice broj: 548148

Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples


Markoč, Zrinka; Hlupić, Nikica; Basch, Danko
Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples // Proceedings of the ITI 2011 33rd International Conference on Information Technology Interfaces / Vesna Luzar-Stiffler, Iva Jarec, Zoran Bekic (ur.).
Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2011. str. 551-556 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 548148 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples

Autori
Markoč, Zrinka ; Hlupić, Nikica ; Basch, Danko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the ITI 2011 33rd International Conference on Information Technology Interfaces / Vesna Luzar-Stiffler, Iva Jarec, Zoran Bekic - Zagreb : Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2011, 551-556

ISBN
978-953-7138-21-9

Skup
ITI 2011 33rd International Conference on Information Technology Interfaces

Mjesto i datum
Cavtat, Hrvatska, 27.06.2011. - 30.06.2011

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
non-technical loss; classification; neural network; sampling

Sažetak
In this paper two different methods for non-technical losses (NTL) detection are analyzed and new approach is proposed, based on the noticed drawbacks. It is shown that NTL can be successfully detected by a neural network trained by “artificial”, i.e., generated samples. This approach eliminates the need for many hard-to-obtain real life samples and the network can easily be trained to detect some new, nontypical occurrences in the system. This makes the proposed solution suitable for large companies that supply many different consumers who possibly change their consumption habits.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekti:
036-0361959-1979 - Oblikovanje i implementacija programskih jezika specijalne namjene (Basch, Danko, MZO ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Danko Basch (autor)

Avatar Url Nikica Hlupić (autor)


Citiraj ovu publikaciju:

Markoč, Zrinka; Hlupić, Nikica; Basch, Danko
Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples // Proceedings of the ITI 2011 33rd International Conference on Information Technology Interfaces / Vesna Luzar-Stiffler, Iva Jarec, Zoran Bekic (ur.).
Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2011. str. 551-556 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Markoč, Z., Hlupić, N. & Basch, D. (2011) Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples. U: Vesna Luzar-Stiffler, Iva Jarec, Zoran Bekic (ur.)Proceedings of the ITI 2011 33rd International Conference on Information Technology Interfaces.
@article{article, author = {Marko\v{c}, Zrinka and Hlupi\'{c}, Nikica and Basch, Danko}, year = {2011}, pages = {551-556}, keywords = {non-technical loss, classification, neural network, sampling}, isbn = {978-953-7138-21-9}, title = {Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples}, keyword = {non-technical loss, classification, neural network, sampling}, publisher = {Sveu\v{c}ili\v{s}ni ra\v{c}unski centar Sveu\v{c}ili\v{s}ta u Zagrebu (Srce)}, publisherplace = {Cavtat, Hrvatska} }
@article{article, author = {Marko\v{c}, Zrinka and Hlupi\'{c}, Nikica and Basch, Danko}, year = {2011}, pages = {551-556}, keywords = {non-technical loss, classification, neural network, sampling}, isbn = {978-953-7138-21-9}, title = {Detection of Suspicious Patterns of Energy Consumption Using Neural Network Trained by Generated Samples}, keyword = {non-technical loss, classification, neural network, sampling}, publisher = {Sveu\v{c}ili\v{s}ni ra\v{c}unski centar Sveu\v{c}ili\v{s}ta u Zagrebu (Srce)}, publisherplace = {Cavtat, Hrvatska} }




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