Zobrazeno 1 - 10
of 13
pro vyhledávání: '"H. Selcuk Nogay"'
Publikováno v:
IEEE Access, Vol 11, Pp 58937-58946 (2023)
Ferroresonance is a non-linear and dangerous resonance phenomenon that can affect power networks and damage electrical equipment. The ferroresonance phenomenon is examined by dividing it into classes, with chaotic ferroresonance being the most danger
Externí odkaz:
https://doaj.org/article/c361d86eda4940afac9ca372c1fead2a
Publikováno v:
Journal of Energy in Southern Africa, Vol 23, Iss 4, Pp 2-7 (2017)
Artificial neural network models were used for short term wind speed forecasting in the Mardin area, located in the Southeast Anatolia region of Turkey. Using data that was obtained from the State Meteorological Service and that encompassed a ten yea
Externí odkaz:
https://doaj.org/article/0f49b1fd9cd04bab80a11f0dcaf20cd5
Autor:
H. Selcuk Nogay
Inorder for vehicle-to-grid (V2G) services to participate in the power and energymarket, they must provide as much aggregated capacity as the market needs. Inorder to provide this capacity, the population of electric vehicle batteries isused. For thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30bb5ae40cd643dcdea41b0fd0b12d27
https://avesis.kayseri.edu.tr/publication/details/c1309818-9184-4a94-8df5-89602ae20bc0/oai
https://avesis.kayseri.edu.tr/publication/details/c1309818-9184-4a94-8df5-89602ae20bc0/oai
Autor:
H. Selcuk Nogay, T. Çetin Akinci
Publikováno v:
Volume: 9, Issue: 1 74-83
European Journal of Technique (EJT)
European Journal of Technique (EJT)
An area's wind speed forecasting is very important to investigate whether the area is available for wind power. The wind speed estimation has been carried out by means of other machine learning methods, mostly artificial neural networks. Because, in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54e963a25d8b033dfd923a5ba83d3e8b
https://doi.org/10.36222/ejt.558914
https://doi.org/10.36222/ejt.558914
Autor:
H. Selcuk Nogay
Publikováno v:
Volume: 6, Issue: 56-59
Balkan Journal of Electrical and Computer Engineering
Balkan Journal of Electrical and Computer Engineering
In this study, ten different types of cancer were classified with deep convolutional neural networks (DCNN). A total of 10,000 MRI (Magnetic Resonance Imaging) data were used for ten cancer patients, including 1000 MRI data for each cancer type. Alth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf8a499b82d1fea666cfc75dd8d59a13
https://doi.org/10.17694/bajece.410250
https://doi.org/10.17694/bajece.410250
Publikováno v:
Archives of Acoustics. 37:279-286
In this study, an artificial neural network application was performed to tell if 18 plates of the same material in different shapes and sizes were cracked or not. The cracks in the cracked plates were of different depth and sizes and were non-identic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cfc72503b0543fefc96059b30b4d6f0
https://doi.org/10.2478/v10168-012-0036-1
https://doi.org/10.2478/v10168-012-0036-1
Akademický článek
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Wind energy has become an important source that has begun to be used for energy in all over the world in recent years. In this study, by examining the wind potential of the western region of Turkey in detail, an analysis was made. The data were provi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86bf0fd07abe3cd1150c34a3e4bd9f76
https://avesis.erciyes.edu.tr/publication/details/06221643-06b9-4cc2-b57b-07d347460410/oai
https://avesis.erciyes.edu.tr/publication/details/06221643-06b9-4cc2-b57b-07d347460410/oai
Publikováno v:
Journal of Energy in Southern Africa, Volume: 23, Issue: 4, Pages: 2-7, Published: 2012
Journal of Energy in Southern Africa, Vol 23, Iss 4, Pp 2-7 (2017)
Journal of Energy in Southern Africa, Vol 23, Iss 4, Pp 2-7 (2017)
Artificial neural network models were used for short term wind speed forecasting in the Mardin area, located in the Southeast Anatolia region of Turkey. Using data that was obtained from the State Meteorological Service and that encompassed a ten yea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::749bbfadd202dd56e7d7ec5c738f8ab6
https://avesis.kayseri.edu.tr/publication/details/ebfddcca-447e-4b52-ab5f-743c280cf8a3/oai
https://avesis.kayseri.edu.tr/publication/details/ebfddcca-447e-4b52-ab5f-743c280cf8a3/oai
Autor:
H. Selcuk Nogay, Tahir Cetin Akinci
This study provides a wind speed estimation of the target station using wind speed data of the neighboring station despite the mountainous structure of the Southeastern Anatolian Region of Turkey. Within the study, a method to determine the wind spee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::542c499f4dda045104491d0234c32509
https://hdl.handle.net/20.500.11857/2964
https://hdl.handle.net/20.500.11857/2964