Modeling of batch processes using explicitly time-dependent artificial neural networks

IEEE Transactions on Neural Networks and Learning Systems

Volumn 25, Issue 5, 2014, Pages 970-979

  Ganesh, Botla ^a   Kumar, Vadlagattu Varun ^a,b   Rani, Kalipatnapu Yamuna ^a  

^a INDIAN INSTITUTE OF CHEMICAL TECHNOLOGY   (India)

^b Rashtriya Chemicals and Fertilizers Limited   (India)

Author keywords

Batch reactor; explicitly time dependent neural networks; modulation function; nonstationary dynamic modeling; semibatch polymerization reactor.

Indexed keywords

BATCH DATA PROCESSING; BATCH REACTORS; DYNAMICS; MODULATION; NETWORK ARCHITECTURE; POLYMERIZATION;

BACKPROPAGATION LEARNING ALGORITHM; BATCH CHEMICAL PROCESS; MODULATION FUNCTIONS; NEURAL NETWORK CONFIGURATIONS; NON-STATIONARY DYNAMICS; POLYNOMIAL COEFFICIENTS; SEMI-BATCH POLYMERIZATION; TIME-DEPENDENT MODULATION;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; HUMAN; NONLINEAR SYSTEM; POLYMERIZATION; TIME;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; POLYMERIZATION; TIME FACTORS;

EID: 84899638352     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2013.2285242     Document Type: Article

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