biblio

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Filters: Author is Tambe, Sanjeev S. and Keyword is genetic programming  [Clear All Filters]
2018
R. Vyas, Bapat, S., Goel, P., Karthikeyan, M., Tambe, S. S., and Kulkarni, B. D., “Application of genetic programming (GP) formalism for building disease predictive models from protein-protein interactions (PPI) data”, IEEE-ACM Transactions on Computational Biology and Bioinformatics, vol. 15, no. 1, pp. 27-37, 2018.
S. Tiwary, Ghugare, S. B., Chavan, P. D., Saha, S., Datta, S., Sahu, G., and Tambe, S. S., “Co-gasification of high ash coal–biomass blends in a fluidized bed gasifier: experimental study and computational intelligence-based modeling”, Waste and Biomass Valorization, vol. 11, no. 1, pp. 1-19, 2018.
2016
S. B. Ghugare and Tambe, S. S., “Development of genetic programming based softsensor model for styrene polymerization process and its application in model based control”, in 2016 Indian Control Conference (ICC), 345 E 47th ST, New York, NY 10017 USA, 2016, pp. 238-244.
V. Patil-Shinde, Saha, S., Sharma, B. K., Tambe, S. S., and Kulkarni, B. D., “High ash char gasification in thermo-gravimetric analyzer and prediction of gasification performance parameters using computational intelligence formalisms”, Chemical Engineering Communications, vol. 203, no. 8, pp. 1029-1044, 2016.
K. Shrinivas, Kulkarni, R. P., Shaikh, S., Ghorpade, R. V., Vyas, R., Tambe, S. S., Ponrathnam, S., and Kulkarni, B. D., “Prediction of reactivity ratios in free radical copolymerization from monomer resonance-polarity (Q-e) parameters: genetic programming-based models”, International Journal of Chemical Reactor Engineering, vol. 14, no. 1, pp. 361-372, 2016.
D. Verma, Goel, P., Patil-Shinde, V., and Tambe, S. S., “Use genetic programming for selecting predictor variables and modeling in process identification”, in 2016 Indian Control Conference (ICC), 345 E 47th ST, New York, NY 10017 USA, 2016, pp. 230-237.
2015
P. Goel, Bapat, S., Vyas, R., Tambe, A., and Tambe, S. S., “Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices”, Journal of Chromatography A, vol. 1420, pp. 98-109, 2015.