ACS Applied Computer Science

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ARTIFICIAL NEURAL NETWORK MODELLING OF CUTTING FORCE COMPONENTS DURING AZ91HP ALLOY MILLING

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The paper presents simulation of the cutting force components for machining of magnesium alloy AZ91HP. The simulation employs the Black Box model. The closest match to (input and output) data obtained from the machining process was determined. The simulation was performed with the use of the Statistica programme with the application of neural networks: RBF (Radial Basis Function) and MLP (Multi-Layered Perceptron). 
  • APA 6th style
Kulisz, M., Zagórski, I., & Semeniuk, A. (2016). Artificial neural network modelling of cutting force components during AZ91HP alloy milling. Applied Computer Science, 12(4), 49-58.
  • Chicago style
Kulisz, Monika, Ireneusz Zagórski, and Aleksandra Semeniuk. "Artificial Neural Network Modelling of Cutting Force Components During Az91hp Alloy Milling." Applied Computer Science 12, no. 4 (2016): 49-58.
  • IEEE style
M. Kulisz, I. Zagórski, and A. Semeniuk, "Artificial neural network modelling of cutting force components during AZ91HP alloy milling," Applied Computer Science, vol. 12, no. 4, pp. 49-58, 2016.
  • Vancouver style
Kulisz M, Zagórski I, Semeniuk A. Artificial neural network modelling of cutting force components during AZ91HP alloy milling. Applied Computer Science. 2016;12(4):49-58.
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