Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Fehim Koylu"'
Autor:
Shakib Abdulahi Osman, Qazwan Abdullah, Nor Shahida Mohd Shah, Fehim Koylu, Ahmed O. Ali, Mohamud M. Hassan, Shipun Hamzah, Abdikarim Abi Hassan, Abdirisak Ali Osman
Publikováno v:
2022 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f74fc1be858a8bc1c49e8f529f6a98bd
https://doi.org/10.1109/itss-ioe56359.2022.9990941
https://doi.org/10.1109/itss-ioe56359.2022.9990941
Publikováno v:
ADI Journal on Recent Innovation (AJRI). 3:36-58
A modified versions of metaheuristic algorithms are presented to compare their performance in identifying the structural dynamic systems. Genetic algorithm, biogeography based optimization algorithm, ant colony optimization algorithm and artificial b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9b0c0d9bc942b751c25b3acf67f56c0
https://doi.org/10.34306/ajri.v3i1.492
https://doi.org/10.34306/ajri.v3i1.492
Autor:
Qazwan Abdullah, Muhiadin M. Sabriye, Abdirisak Ali Osman, Fehim Koylu, Mohamud M. Hassan, Ahmed O. Ali, Ali Ammar Hilal
Publikováno v:
2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA).
In recent years, the Internet of Things (IoT) has received a lot of research attention. The IoT is considered part of the Internet of the future and is made up of billions of intelligent communication “things”. The future of the Internet will con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cde9f4de476fb2a9030ac21ffc9b191
https://doi.org/10.1109/esmarta52612.2021.9515748
https://doi.org/10.1109/esmarta52612.2021.9515748
Autor:
Fehim Koylu
Publikováno v:
2017 8th International Conference on Information Technology (ICIT).
Data mining is the process of extracting a meaningful information from raw data. Classical data mining algorithms can be used to extract an offline static model for classification problems which has a collected dataset. Unfortunately, Offline algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d7a2540d5307411c1745c08741c7764
https://doi.org/10.1109/icitech.2017.8079922
https://doi.org/10.1109/icitech.2017.8079922
In data mining, classification rule learning extracts the knowledge in the representation of IF_THEN rule which is comprehensive and readable. It is a challenging problem due to the complexity of data sets. Various meta-heuristic machine learning alg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a316374f028fee474191cfd941cad6d0
https://avesis.erciyes.edu.tr/publication/details/5ad5f207-f573-47b3-a459-bd690c512b3c/oai
https://avesis.erciyes.edu.tr/publication/details/5ad5f207-f573-47b3-a459-bd690c512b3c/oai
Data mining aims to discover interesting, non-trivial, and meaningful information from large datasets. One of the data mining tasks is classification, which aims to assign the given datasets to the most suitable classes. Classification rules are used
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c118801a424a9ee3ec4b690b2df2eca7
https://avesis.erciyes.edu.tr/publication/details/99aa3dba-c69d-40a3-9fdf-bbc3dc48e233/oai
https://avesis.erciyes.edu.tr/publication/details/99aa3dba-c69d-40a3-9fdf-bbc3dc48e233/oai
Autor:
Mustafa Danacı, Fehim Koylu
Publikováno v:
Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, 2005..
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad3a92b9f4d1fd61d4f5b93fafe5bb32
https://doi.org/10.1109/siu.2005.1567761
https://doi.org/10.1109/siu.2005.1567761
Autor:
Fehim Koylu, Veysel Aslantas
Publikováno v:
Proceedings of the IEEE 13th Signal Processing and Communications Applications Conference, 2005..
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c777dc33c8d5d7c3c576544178d056e8
https://doi.org/10.1109/siu.2005.1567768
https://doi.org/10.1109/siu.2005.1567768