A Novel, Nelder-Mead Optimization Approach, based on Neuro-regression modeling for the Energy Efficiency Parameters of End Milling Process

ŞEYDA İŞBİLİR

Global crises are increasing day by day due to the rapid depletion of energy supplies around the planet. One of the goals of engineering is to prevent this situation by developing innovative solutions to this rapid energy consumption that has disappeared in the world. A solution could be to reduce the energy consumption of the machines that are used during production. In this study, a new design technique based on the neuro-regression approach and non-linear regression modeling was offered as an alternative to Taguchi design to reduce energy consumption. Thus, a cutting parameter optimization ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 9 - 105 29 Görüntülenme

Erişime Açık

Optimization of Process Parameters for Green Composites in Abrasive Water Jet Machining Process Using Neuro-Regression Analysis

LEVENT AYDIN

Kaynakça var.

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 7 - 79 54 Görüntülenme

Erişime Açık

Modeling and optimum design for wire electrical discharge machining of γ titanium aluminide alloy

ÖMER FARUK BÜYÜKYAVUZ

Wire electrical discharge machining (WEDM) of γ titanium aluminide is the subject of the current research. Due to the large number of process variables and sophisticated stochastic process mechanisms, selecting the best machining parameter combinations for increased cutting efficiency and accuracy is a difficult task in WEDM. In general, there is no perfect combination that can produce the fastest cutting speed and the finest surface finish quality at the same time. For this purpose, the data were selected from a literature study. This study describes an attempt to devise a suitable machining ...Daha fazlası

Makale 2021 Journal of Artificial Intelligence and Data Science1 ( 1 ) , pp. 8 - 95 28 Görüntülenme