Page 317 - Data Science Algorithms in a Week
P. 317
298 Jose M. Prieto
Nissen, S. (2007). Fast Artificial Network Library http://leenissen.dk/fann/
Ozturk, I., Tornuk, F., Sagdic, O., & Kisi, O. (2012). Application of non-linear models to
predict inhibition effects of various plant hydrosols on Listeria monocytogenes
inoculated on fresh-cut apples. Foodborne Pathog Dis., 9, 607-616.
Palancar, M., Aragón, J., & Torrecilla J. (1998). pH-Control system based on artificial
neural networks. Ind. Eng. Chem. Res., 37(7), 2729-2740.
Parojcić, J., Ibrić, S., Djurić, Z., Jovanović, M., & Corrigan O. (2007). An investigation
into the usefulness of generalized regression neural network analysis in the
development of level A in vitro-in vivo correlation. Eur J Pharm Sci., 30, 264-272.
Pei, R., Zhou, F., Ji, B., & Xu, J. (2009). Evaluation of combined antibacterial e ects of
eugenol, cinnamaldehyde, thymol, and carvacrol against E. coli with an improved
method, J Food Sci, 74, M379–M383.
Rahman, A., Afroz, M., Islam, R., Islam, K., Amzad Hossain, M., & Na, M. (2014). In
vitro antioxidant potential of the essential oil and leaf extracts of Curcuma zedoaria
Rosc. J Appl. Pharm Sci, 4, 107-111.
Ruan, R., Almaer, S., & Zhang, S. (1995). Prediction of dough rheological properties
using neural networks. Cereal Chem, 72(3), 308-311.
Sagdic, O., Ozturk, I., & Kisi, O. (2012). Modeling antimicrobial effect of different grape
pomace and extracts on S. aureus and E. coli in vegetable soup using artificial neural
network and fuzzy logic system. Expert Systems Applications, 39, 6792-6798.
Shahidi, F. (2000). Antioxidants in food and food antioxidants. Nahrung, 44, 158–163.
Sharma, A., Mann, B., & Sharma, R. (2012). Predicting antioxidant capacity of whey
protein hydrolysates using soft computing models. Advances in Intelligent and Soft
Computing, 2, 259-265.
Tanir, A. & Prieto, J. (2016). Essential Oils for the Treatment of Herpes Virus Infections:
A Critical Appraisal Applying Artificial Intelligence and Statistical Analysis Tools.
Unpublished results.
Torrecilla, J., Mena, M., Yáñez-Sedeño, P., & García J. (2007). Application of artificial
neural networks to the determination of phenolic compounds in olive oil mill
wastewater. J Food Eng, 81, 544-552.
Torrecilla, J., Otero, L., & Sanz, P. (2004). A neural network approach for
thermal/pressure food processing. J Food Eng, 62, 89-95.
Usami, A, Motooka R, Takagi A, Nakahashi H, Okuno Y, & Miyazawa M. (2014).
Chemical composition, aroma evaluation, and oxygen radical absorbance capacity of
volatile oil extracted from Brassica rapa cv. “yukina” used in Japanese traditional
food. J Oleo Sci, 63, 723-730.
Wang, H., Wong, H., Zhu, H., & Yip, T. (2009). A neural network-based biomarker
association information extraction approach for cancer classification. J Biomed
Inform, 42, 654-666.
Yalcin, H., Ozturk, I., Karaman, S., Kisi, O., Sagdic, O., & Kayacier, A. (2011).
Prediction of effect of natural antioxidant compounds on hazelnut oil oxidation by