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FUZZY LOGIC AND NEURAL NETWORK CONTROL OF INDUSTRIAL THERMAL SYSTEMS
NUMERICAL TECHNIQUES IN MODELING AND SIMULATION OF SEMICONDUCTOR
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algorithm analysis application approach approximately artificial neural networks autocorrelation bond graph calculations Clark County components computation control charting convergence cost curve CUSUM data set defined determine distribution dynamic economic development effect efficiency eigenvalues eigenvectors elements emissions Engineering equations error estimate example execution exponential factors Figure flow FORTRAN function fuzzy fuzzy set given identified IEEE impact implementation increase input integrated interconnections Laplace's equation leadership linear matrix maximum MAXNET measure method methodology minterms neuron model nodes number of processes obtained operations optimal output paper parameters performance Petri Petri nets PID controller Pittsburgh problem procedure production random random variables region response root transputer sample Session Chairman shown sigmoid sigmoid function signal simulation software engineering solution statistics structure techniques Technology theorems transformation University University of Pittsburgh utilized values variables vector wavelet weights zero