Volodymyr Dahl East-Ukrainian National University, Radyansky pr. 59-a, Severolonetsk, 93406, Ukraine
Bibliografia
1. Afanasenko A.G., Verevkin A.P., 2009.: Neuronet simulation of carbonation process quality rating . VestnikU. ,Vol. 13 №2 (35), 222-225.
2.Baskin I.I., Palyulin V.A., Zefirov N.S., 2006.: Multilayered perceptrons in "structure-property" relationship studies for organic compounds. Rus. Chem. Journ. ( Journal of Russian chemical society after D. I. Mendeleyev)., T. L. №2., 86-96.
3.Baskin I.I., Palyulin V.A., Zefirov N.S., 2005.: Using artificial neural networks for chemical compounds properties prognostication. Neural computers: design, applications, № 1-2, 98-101.
4.Baskin I.I., Skvortsova M.I., Palyulin V.A., Zefirov N.S., 1997.: Quantitative chemical structure-property/activity relationship studies using artificial neural networks. Foundations of computing and decision sciences. Vol. 22, №2, 107-116.
5.De Souza, M. В., Pinto J. C., et al., 1996:. Control of a chaotic polymerization reactor: A neural network based model predictive approach. Polymer Engineering and Science, 36(4), 448-457.
6.Galushkin A.I., 2000.: The book. Theory of neural networks. M.: I, 416.
7.Gardner J.W., Hines E.L., Wilkinson M., 1990.: Application of artificial neural networks to an electronic olfactory system. Measurement science and technology. Vol. 1, 446-451.
9.Hong H.-K., Kwon C.N., Kim S.-R., 2000.: Portable electronic nose system with gas sensor array and artificial neural network. Sensors and Actuators B. , Vol. 66, 49-52.
10.Huang, Y. F., G. H. Huang, et al., 2003.: Development of an artificial neural network model for predicting minimum miscibility pressure in ACETIC ACID SYNTHESIS UNIT WHILE START-UP 191 C02 flooding. Journal of Petroleum Science and Engineering, 37(1-2), 83-95.
14.Kusz A., Maksym P., Marciniak A.W., 2011.: Bayesian networks as knowledge representation system in domain of reliability engineering. TEKA Commission of Motorization I Energ. Roln., 11 C, 173-180.
16.Larachi F. and Granjean B. P. A., 2000.: Comments on "Neural network modeling of structured packing height equivalent to a theoretical plate" and "HETP and pressure drop prediction for structured packing distillation columns using a neural network". Industrial & Engineering Chemistry Research, 39(11), 44374437.
17.Medvedev V.S., Potemkin V.G., 2002.: The book, Neural networks. MATLAB 6. Under the editorship of Cand. of Sc. Potemkin V.G., M.: DIALOG IEFI, 495.
18.Nagy Z., American Institute of Chemical Engineers., et al., 2000.: A Comparison of First Principles and Neural Network Model Based Nonlinear Predictive Control of a Distillation Column. Distributed by American Institute of Chemical Engineers, New York, N. Y.
19.Park J.-K., 1993.: Modeling of Distillation Column and Reactor Dynamics Using Artificial Neural Networks (Neural Networks). DAI- 55, №., 01B, 6660.
20.Sabharwal A., 1998.: A Hybrid Approach Applied to an Industrial Distillation Column That Compares Physical and Neural Network Modeling Techniques. MAI, 37, no. 02, 0648.
21.Santos V. M. L., Carvalho F. R., et al., 2000.: Predictive control based on neural networks: An application to a fluid catalytic cracking industrial unit. Brazilian Journal of Chemical Engineering, 17(4-7), 897-905.
22.Su G. H., Fukuda K., et al. 2002.: Application of an artificial neural network in reactor thermohydraulic problem: Prediction of critical heat flux. Journal of Nuclear Science and Technology, 39(5), 564-571.
23.Su G. H., Fukuda K., et al. 2002.: Applications of artificial neural network for the prediction of flow boiling curves. Journal of Nuclear Science and Technology, 39(11), 1190-1198.