Abstract
The most widely and well known machining process used is turning. The turning process possesses higher complexity and uncertainty and therefore several empirical modelling techniques such as artificial neural networks, regression analysis, fuzzy logic and support vector machines have been used for predicting the performance of the process. This paper reviews the applications of empirical modelling techniques in modelling of turning process and unearths the vital issues related to it.
| Original language | English |
|---|---|
| Pages (from-to) | 121-129 |
| Number of pages | 9 |
| Journal | International Journal of Modelling, Identification and Control |
| Volume | 20 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2013 |
| Externally published | Yes |
Keywords
- ANN
- Artificial neural network
- Empirical
- Genetic programming
- Modelling
- Regression analysis
- Review
- Support vector machines
- SVM
- Turning