Genetically evolved radial basis function network based prediction of drill flank wear

Engineering Applications of Artificial Intelligence

Volumn 23, Issue 7, 2010, Pages 1112-1120

  Garg, Saurabh ^a   Patra, Karali ^b   Khetrapal, Vishal ^c   Pal, Surjya K ^c   Chakraborty, Debabrata ^d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b INDIAN INSTITUTE OF TECHNOLOGY PATNA   (India)

^c INDIAN INSTITUTE OF TECHNOLOGY   (India)

^d INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI   (India)

Author keywords

Drilling; Flank wear; Genetic algorithm; Radial basis function network; Self growing algorithm

Indexed keywords

COMPUTATIONALLY EFFICIENT; DRILLING HOLES; DRILLING PROCESS; ERROR MINIMIZATION; FLANK WEAR; HIDDEN LAYERS; HIGH-SPEED STEELS; K-MEANS CLUSTERING ALGORITHM; RADIAL BASIS FUNCTIONS; SELF GROWING ALGORITHM; TRAINING PROCEDURES; TWO STAGE; UNSUPERVISED TRAINING; WORK PIECES;

ATTITUDE CONTROL; DRILLS; GENETIC ALGORITHMS; IMAGE SEGMENTATION; NETWORK ARCHITECTURE; NETWORK PERFORMANCE; OPTIMIZATION; RADIAL BASIS FUNCTION NETWORKS;

CLUSTERING ALGORITHMS;

EID: 77957872563     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2010.02.012     Document Type: Article

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