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- W846272364 abstract "Roughness obtained in honing process depends on many different process parameters, such as grainsize of abrasive stones, pressure of stones on the workpiece’s surface, density of abrasive, tangentialspeed of the honing head and linear speed of the honing head. This fact makes it difficult to study theprocess from an analytical point of view. For this reason, use of empirical methods or use of artificialintelligence is recommended in this case. In the present paper, results about use of neural networks forobtaining average roughness Ra as a function of honing parameters are presented. Best neuralnetwork was chosen among different possibilities. For doing this, experimental results were dividedinto three groups: 70 % of results were used for training, 15 % of results were used for validation and15 % of results were used as test to compare networks with other models. The best neural network wasconsidered to be the one with lowest errors using the validation experimental results." @default.
- W846272364 created "2016-06-24" @default.
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- W846272364 date "2013-01-01" @default.
- W846272364 modified "2023-09-27" @default.
- W846272364 title "Selection of a neural network for modelling the honing process" @default.
- W846272364 hasPublicationYear "2013" @default.
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