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Original Articles

Modeling Thermal Conductivity, Specific Heat, and Density of Milk: A Neural Network Approach

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Pages 531-539 | Received 02 Mar 2003, Accepted 04 Sep 2003, Published online: 06 Feb 2007

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Amélie Deglaire, Jeehyun Lee, Luca Lanotte, Thomas Croguennec, Cécile Le Floch-Fouéré, Romain Jeantet, Nadia Berkova, Frédérique Pédrono, Yves Le Loir, Didier Dupont, Geneviève Gésan-Guiziou & Sergine Even. (2023) Towards more biomimetic and sustainable infant formula: challenges and future opportunities. Trends in Food Science & Technology 137, pages 109-123.
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Robert Sevenich. 2022. Encyclopedia of Dairy Sciences. Encyclopedia of Dairy Sciences 336 355 .
Khadijeh Firoozirad, Avinash Alagumalai, Evgeny Solomin, Fan Fangfang, Ho Seon Ahn & Omid Mahian. (2021) Study on thermophysical properties of alumina nanoparticles enhanced ionic liquids (NEILs): A modeling approach. Journal of Molecular Liquids 332, pages 115827.
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Da-Wen SunAdriana Delgado, Da-Wen Sun & Amelia Rubiolo. 2012. Thermal Food Processing. Thermal Food Processing 3 32 .
Giovanni A. Longo, Claudio Zilio, Elena Ceseracciu & Monica Reggiani. (2012) Application of Artificial Neural Network (ANN) for the prediction of thermal conductivity of oxide–water nanofluids. Nano Energy 1:2, pages 290-296.
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Bağdagül Karaağaç, Melih İnal & Veli Deniz. (2012) Predicting optimum cure time of rubber compounds by means of ANFIS. Materials & Design 35, pages 833-838.
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Bağdagül Karaağaç, Melih İnal & Veli Deniz. (2009) Artificial neural network approach for predicting optimum cure time of rubber compounds. Materials & Design 30:5, pages 1685-1690.
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Federico Marini. (2009) Artificial neural networks in foodstuff analyses: Trends and perspectives A review. Analytica Chimica Acta 635:2, pages 121-131.
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E.C. Gonçalves, L.A. Minim, J.S.R. Coimbra & V.P.R. Minim. (2005) Modeling sterilization process of canned foods using artificial neural networks. Chemical Engineering and Processing: Process Intensification 44:12, pages 1269-1276.
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