An artificial neural network approach to multiple-response optimization

International Journal of Advanced Manufacturing Technology

Volumn 40, Issue 11-12, 2009, Pages 1227-1238

  Noorossana, R ^a   Davanloo Tajbakhsh, Sam ^a   Saghaei, A ^b  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Artificial neural networks; Design of experiment; Genetic algorithm, multiple layer perceptron; Mean square error; Radial basis function; Response surface methodology

Indexed keywords

ATTITUDE CONTROL; BACKPROPAGATION; BLOCK CODES; DESIGN OF EXPERIMENTS; GENETIC ALGORITHMS; GENETIC ENGINEERING; MATHEMATICAL MODELS; MEAN SQUARE ERROR; OPTIMIZATION; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; SURFACE PROPERTIES; TEXTILE INDUSTRY; TEXTILE PROCESSING;

ALTERNATIVE APPROACHES; ARTIFICIAL NEURAL NETWORK APPROACHES; ARTIFICIAL NEURAL NETWORKS; CONTROL FACTORS; DESIRABILITY FUNCTIONS; MULTIPLE RESPONSE; OPTIMAL SETTINGS; OPTIMIZATION METHODS; POLYNOMIAL REGRESSION MODELS; QUALITATIVE RESPONSE; RADIAL BASIS FUNCTION; RESPONSE FUNCTIONS; RESPONSE SURFACE METHODOLOGY;

NEURAL NETWORKS;

EID: 60749101906     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-008-1423-7     Document Type: Article

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