Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Ebun Fasina"'
Autor:
Babatunde Alade Sawyerr, Ebun Fasina, Wasiu Oyediran Adedeji, Mofoluso Kehinde Adeniran, Sunday Ayoola Oke, John Rajan
Publikováno v:
Journal of Engineering and Applied Science, Vol 70, Iss 1, Pp 1-20 (2023)
Abstract The objective of this study is to propose a method called the fuzzy technique for order preference by similarity to the ideal solution (F-TOPSIS) to select parameters of the wire electrical discharge machining (WEDM) process. Consequently, t
Externí odkaz:
https://doaj.org/article/53079a60afa9443d8e0fc63870942798
Publikováno v:
Journal of Engineering and Applied Science, Vol 70, Iss 1, Pp 1-23 (2023)
Abstract The expanding proliferation of components for engineering applications requires greater optimisation of parameters, which consequently increases the need for more efficient boring practices. The Taguchi Pareto-Box Behnken design is an effect
Externí odkaz:
https://doaj.org/article/aca86da1999c4bf8a6abe87d71ae72ed
Autor:
Meshach Chukwuebuka Ikedue, John Rajan, Sunday Oke, Ebun Fasina, Babatunde Alade Sawyerr, Wasiu Oyediran Adedeji
Publikováno v:
Journal of Applied Science & Process Engineering, Vol 10, Iss 2 (2023)
Despite being contemporary, the wire electrical discharge machining (EDM) industry is burdened with complicated and challenging problems. However, the double optimisation method involving Taguchi analyses and genetic algorithms is a powerful tool to
Externí odkaz:
https://doaj.org/article/32b16db180db4c6699c55d318ee6dc2d
Autor:
Ebun Fasina, Babatunde Alade Sawyerr, Wasiu Oyediran Adedeji, Kasali Aderinmoye Adedeji, Ridwan Majekodunmi Adegoke, Sunday Ayoola Oke, Elkanah Olaosebikan Oyetunji
Publikováno v:
Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ, Vol 14, Iss 2, Pp 71-104 (2023)
A previous study has shown the successful application of the Taguchi method in both the direct and indirect perspectives to compute the optimal parameters during the turning of Inconel x-750 alloy. The study deployed signal-to-noise ratios to minimiz
Externí odkaz:
https://doaj.org/article/ff8b44af371b4713bed4f1ee5c69d762
Autor:
Babatunde Alade Sawyerr, Ebun Fasina, Wasiu Oyediran Adedeji, Mofoluso Kehinde Adeniran, Sunday Ayoola Oke, John Rajan
Publikováno v:
Journal of Engineering and Applied Science, Vol 70, Iss 1, Pp 1-2 (2023)
Externí odkaz:
https://doaj.org/article/6f43f1aadf8440d98a0047425d4a2521
Autor:
Adetayo Moses Bamidele, Sunday Ayoola Oke, John Rajan, Babatunde Alade Sawyerr, Ebun Fasina, Kasali Aderinmoye Adedeji, Elkanah Olaosebikan Oyetunji
Publikováno v:
IJIEM - Indonesian Journal of Industrial Engineering and Management. 4:61
It is difficult to improve the quality of friction stir welded joints of AA5052-H32 material because of scarce metrics on its concurrent optimization and prioritization. However, the objective of this article is to obtain optimal parametric values an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b5ccc5fab5291233b8f4ca6058396cf
https://doi.org/10.22441/ijiem.v4i1.18403
https://doi.org/10.22441/ijiem.v4i1.18403
Publikováno v:
Studies in Computational Intelligence ISBN: 9783030378295
Deep learning in recent times has become a hugely active area within machine learning. Its popularity can be attributed to the huge successes recorded by various deep learning algorithms, notably convolutional neural networks (CNNs), in various ident
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::633394ff89487547d9198fda0ba0e28c
https://doi.org/10.1007/978-3-030-37830-1_8
https://doi.org/10.1007/978-3-030-37830-1_8
Autor:
Sawyerr, Babatunde Alade, Fasina, Ebun, Adedeji, Wasiu Oyediran, Adeniran, Mofoluso Kehinde, Oke, Sunday Ayoola, Rajan, John
Publikováno v:
Journal of Engineering & Applied Science; 10/25/2023, Vol. 70 Issue 1, p1-2, 2p
Autor:
Sawyerr, Babatunde Alade, Fasina, Ebun, Adedeji, Wasiu Oyediran, Adeniran, Mofoluso Kehinde, Oke, Sunday Ayoola, Rajan, John
Publikováno v:
Journal of Engineering & Applied Science; 10/6/2023, Vol. 70 Issue 1, p1-20, 20p
Publikováno v:
Journal of Engineering & Applied Science; 5/18/2023, Vol. 70 Issue 1, p1-23, 23p