Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi-genetic learning algorithm

Expert Systems with Applications

Volumn 36, Issue 2 PART 2, 2009, Pages 3216-3222

  Ho, Wen Hsien ^a   Tsai, Jinn Tsong ^b   Lin, Bor Tsuen ^c   Chou, Jyh Horng ^c  

^a KAOHSIUNG MEDICAL UNIVERSITY   (Taiwan)

^b NATIONAL PINGTUNG UNIVERSITY   (Taiwan)

^c NATIONAL KAOHSIUNG UNIVERSITY OF APPLIED SCIENCES   (Taiwan)

Author keywords

Adaptive network based fuzzy inference system; End milling process; Hybrid Taguchi genetic learning algorithm; Surface roughness

Indexed keywords

FORECASTING; FUZZY INFERENCE; FUZZY LOGIC; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; INFERENCE ENGINES; INTELLIGENT CONTROL; MEAN SQUARE ERROR; MEMBERSHIP FUNCTIONS; MILLING (MACHINING); SURFACE ROUGHNESS;

ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM; ANFIS METHOD; END-MILLING PROCESS; GENETIC LEARNING ALGORITHMS; HYBRID TAGUCHI-GENETIC LEARNING ALGORITHM; MATLAB TOOLBOXES; PREDICTION ACCURACY; ROOT MEAN SQUARED ERRORS;

LEARNING ALGORITHMS;

EID: 56349089474     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.01.051     Document Type: Article

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