Analysis of Sensor Data for Hydrogen Production in a Biofilm Photoreactor Using Multilayer Perceptron Network
Keywords:
Neural Networks, Hydrogen Production, Data AnalysisAbstract
Neural Networks are one of the most appreciate techniques in the field of the analysis of the data set. In this paper the usage of multilayer perceptron networks (MLP) for the prediction of the hydrogen production from the sensor data is presented. The results with R2 value of over 0.95 show clearly, that it is possible to build an effective system for the prediction of the hydrogen production and concentration rates based only on the data covering biofilm thickness.References
Nelles O., Nonlinear system identification: from classical approaches to neural networks and fuzzy models. Springer Publishing, New York, 2001.
Kilimann, H.C., Delgado A., Vogel R.F., Gänzle M.G., A fuzzy Logic based model for the multi-stage high pressure inactivation of Lactococcuslactisssp. cremorisMG 1363. Int J Food Microbiol., 2005. 98: p. 89-105.
Bening R.M., B.T.M., Delgado A., Initial studies of predicting flow fields with an ANN hybrid. Advances in engineering software 2001. 32(12): p. 895-901.
Diez L., Z.B.E., Kowalczyk W., Delgado A., Investigation of multiphase flow in sequencing batch reactor (SBR) by means of hybrid methods. Chemical Engineering Science 2007. 62(6): p. 1803-1813.
Chen, T.C., H., Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems. IEEE Transactions on Neural Networks, 1995. 6(4): p. 911-917.
Cybenko, G., Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals, and Systems, 1989. 3: p. 303-314.
Hornik, K., Approximation capabilities of multilayer feedforward neural networks. Neural Networks, 1990. 4: p. 251-257.
Hornik, K., Some new results on neural network approximation. Neural Networks, 1993. 6: p. 1069-1072.
Leshno, M., Lin, V., Pinkus, A., & Shochen, S., Multilayer feedforward networks with a polynomial activation function can approximate any function. Neural Networks, 1993. 6: p. 861-867.
Scarselli F., T., Ah Chung, Universal Approximation Using Feedforward Neural^Networks: A Survey of Some Existing Methods and Some New Results. Neural Networks, 1998. 11(1): p. 15-37.
Yi Liao, S.-C.F., Henry L.W. Nuttle, Relaxed conditions for radial-basis function networks to be universal approximators. Neural Networks, 2003. 16: p. 1019-1028.
Widrow, B., 30 years of adaptive neural networks: Perceptron, Madaline and Backpropagation. IEEE Transactions on Neural Networks, 1990. 78(9): p. 1415-1442.
Turkia, H., Sirén H., Pitkänen J.P., Wiebe M., Penttilä M., Capillary electrophoresis for the monitoring of carboxylic acid production by gluconobacter oxydans. J Chromatogr A, 2010(1217): p. 1537-1542.
Argun H., K.F., Kapdan I.K., Oztekin R., Batch dark fermentation of powdered wheat starch to hydrogen gas: effects of the initial substrate and biomass concentrations. International Journal of Hydrogen Energy, 2008. 33: p. 6109-6115.
Zeng M., S.A., Roche N., Calibration of hydrodynamic behavior and biokinetics for TOC removal modeling in biofilm reactors under different hydraulic conditions. Bioresour Technol, 2013. 144: p. 202-209.
Liao Q., Z.N., Zhu X., Huang Y., Chen R., Enhancement of hydrogen production by optimization of biofilm growth in a photobioreactor. International Journal of Hydrogen Energy, 2015. 40: p. 4741-4751.
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