Sztuczne sieci neuronowe jako nadrzędzie w technologii żywności

• Autorzy: Balejko, J. A.
• Języki publikacji: PL

Słowa kluczowe

PL

sztuczne sieci neuronowe; technologia żywności

EN

artificial neural networks; food technology

• Czasopismo: LAB Laboratoria, Aparatura, Badania
• Rocznik: 2007
• Tom: R. 12, nr 1
• Strony: 44-46
• Opis fizyczny: 51 Bibliogr. 14 poz.

Twórcy

autor

Balejko, J. A.

Bibliografia

• 1. Boccorh R.K., Peterson A.: An artificial neural network model for prediction flavour intensity in blackcurrant concentrates. Food Quality and preference 13 (2002) 117-128.
• 2. Bomio, M.: Neural networks and the future of sensory evaluation. Food Technology. Volume 52, Issue 8, August 1998, Pages 62-63.
• 3. Czapski J., Limanówka-Jacygrad D.: Zastosowanie sieci neuronowych do przewidywania oceny barwy soków na podstawie pomiarów instrumentalnych. XXVII Sesja Naukowa Technologii i Chemii Żywności PAN
• 4. Fang Q., Biby G., Haque E., Hanna M.A. , Spillman C.K.: Neural network modeling of physical properties of ground wheat. Cereal Chemistry Volume 75, Issue 2, March 1998, Pages 251-253.
• 5. Garcia-Gimeno RM, Hervas-Martinez C., de Siloniz MI.: Improving artificial neural networks with a pruning methodology and genetic algorithms for their application in microbial growth prediction in food. International Journal of Food Microbiology 72 (2002)19-30.
• 6. Haugen J-E., Kvaal K.: Electronic nose and artificial neural network. MATFORSK, Norwegian Food Research Institute, Osloveien 1, N-1430A°s. Hussain M.A., Shafiur Rahman M., Ng C.W.: Prediction of pores formation (porosity) in foods during drying generic models by the use of hybrid neural network. Journal of Food Engineering 51 (2002), 239-248.
• 7. Lednicky P., Meszaros A.: Neural network modeling in optimization of continuous fermentation processes. Bioprocess Engineering, Springer-Verlag 1998,18 (1998) 427-432
• 8. Morimoto T., Purwanto W., Suzuki J., Hashimoto Y.: Optimization of heat treatment for fruit during storage using neural networks and genetic algorithms. Computers and Electronics in Agriculture 19 (1997)87-101.
• 9. Ni, H., Gunasekaran, S.: Food quality prediction with neural networks, Food Technol. 1998. 52 pp. 60-65.
• 10. Rai P., Majumdar G.C., Das-Gupta S., De S.: Prediction of the viscodity of clarified fruit juice using artificial neural network: a combined effect of concentration and temperature. Journal of Food Engineering 68 (2005), 527-533.
• 11. Raptis C.G., Siettos C.I., Kiranoudis C.T., Bafas G.V.: Classification of aged wine distillates using fuzzy and neural network systems. Journal of Food Engineering 46 (2000) 267-275.
• 12. Sakovic-Stefanovic J.: Neural net controller by inverse modeling for a distillation plant. Computers Chem. Engng. 1996, vol. 20, pp 925-930.
• 13. Torrecilla J.S, Otero L., Sanz P.D.: Artificial neural networks: a promising tool to design and optimize high-pressure food processes. Journal of Food Engineering. Vol: 69, 3, August, 2005. pp: 299-306.
• 14. Welyi-Chanes J., Vergara-Balderas F., Bermudez-Agu-irre D.: Transport phenomena in food engineering: basic concepts and advances. Journal of Food Engineering 67, 2005.113-128