Молимо вас користите овај идентификатор за цитирање или овај линк до ове ставке:
https://open.uns.ac.rs/handle/123456789/12049
Назив: | Modelling and Optimization of Surface Roughness Parameters of Stainless Steel by Artificial Intelligence Methods | Аутори: | Kovač P. Savković, Borislav Rodić D. Aleksić A. Gostimirović, Marin Sekulić M. Kulundžić, Nenad |
Датум издавања: | 1-јан-2020 | Часопис: | Lecture Notes in Mechanical Engineering | Сажетак: | © 2020, Springer Nature Switzerland AG. The objective of this study is to examine the influence of machining parameters on surface finish in turning of medical steel. A new approach in modeling surface roughness which uses design of experiments is described in this paper. The values of surface roughness predicted by different models are then compared. Used were adaptive-neuro-fuzzy-inference system (ANFIS). The results showed that the proposed system can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments with central composition plan modeling technique can be effectively used for the prediction of the surface roughness for medical steel difficult to machining. Optimizations of surface roughness parameters was done by use of ant colony method. | URI: | https://open.uns.ac.rs/handle/123456789/12049 | ISBN: | 9783030313425 | ISSN: | 21954356 | DOI: | 10.1007/978-3-030-31343-2_1 |
Налази се у колекцијама: | FTN Publikacije/Publications |
Приказати целокупан запис ставки
SCOPUSTM
Навођења
2
проверено 14.09.2022.
Преглед/и станица
23
Протекла недеља
12
12
Протекли месец
0
0
проверено 10.05.2024.
Google ScholarTM
Проверите
Алт метрика
Ставке на DSpace-у су заштићене ауторским правима, са свим правима задржаним, осим ако није другачије назначено.