Genetic based approach to predict surface roughness

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Brezocnik:2004:TMT,

• author = "Miran Brezocnik and Mirko Ficko and Miha Kovacic",
• title = "Genetic based approach to predict surface roughness",
• booktitle = "8th International Research/Expert Conference Trends in the Development Machinery and Associated Technology",
• year = "2004",
• pages = "91--94",
• address = "Neum, Bosnia and Herzegovina",
• month = "15-19 " # sep,
• keywords = "genetic algorithms, genetic programming, celno frezanje, povrsinska hrapavost, napoved hrapavosti, genetsko programiranje, end milling, surface roughness, prediction of surface roughness",
• ISBN = "9958-617-21-8",
• URL = "http://cobiss.izum.si/scripts/cobiss?command=DISPLAY&base=COBIB&RID=9009686",
• URL = "https://plus.cobiss.si/opac7/bib/9009686",
• abstract = "In this paper we propose genetic programming to predict surface roughness in end milling. Two independent data sets were obtained from measurements: the training data set and the testing data set. Spindle speed, feed rate, depth of cut and vibrations were used as independent input variables (parameters), while surface roughness was the output variable. Different surface roughness models were obtained with the training data set and genetic programming. The testing data set was used to prove the accuracy of the best model. The conclusion is that surface roughness is most influenced by the feed rate, while vibrations increase the prediction accuracy.",
• jaezik = "angleski",
• notes = "Paper number TMT04-237 http://www.mf.unze.ba/tmt2004/submittedabstracts2.htm (broken) COBISS.SI-ID: 9009686",

}

Genetic Programming entries for Miran Brezocnik Mirko Ficko Miha Kovacic

Citations