The selection of milling parameters by the PSO-based neural network modeling method

International Journal of Advanced Manufacturing Technology

Volumn 57, Issue 1-4, 2011, Pages 49-60

  Farahnakian, Masoud ^a   Razfar, Mohammad Reza ^a   Moghri, Mahdi ^b   Asadnia, Mohsen ^c  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

^c Iran University of Industries and Mines   (Iran)

Author keywords

Artificial neural network; Milling; Particle swarm optimization; Polyamide 6 nanoclay

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CUTTING FORCES; CUTTING PARAMETERS; END MILL; EXPERIMENTAL ALGORITHMS; EXPERIMENTAL MEASUREMENTS; FEED-RATES; HIGH-SPEED STEELS; MILLING PARAMETERS; NANO CLAYS; NEURAL NETWORK MODELING; PARTICLE SWARM; PARTICLE SWARM OPTIMIZATION ALGORITHM; PERSONALIZED PRODUCTS; POLYAMIDE 6; POLYMER NANOCOMPOSITE; RESEARCH AND DEVELOPMENT; SPINDLE SPEED;

ALGORITHMS; COMPOSITE MATERIALS; MILLING (MACHINING); NANOCOMPOSITES; PARTICLE SWARM OPTIMIZATION (PSO); POLYMERS; SURFACE ROUGHNESS; SURFACES;

NEURAL NETWORKS;

EID: 80053573850     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-011-3262-1     Document Type: Article

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