Comparison of adaptive neuro-fuzzy inference system and artificial neural networks (MLP and RBF) for estimation of oxidation parameters of soybean oil added with curcumin

Journal of Food Measurement and Characterization

Volumn 9, Issue 2, 2015, Pages 215-224

  Asnaashari, Elahe ^a   Asnaashari, Maryam ^b   Ehtiati, Ahmad ^c   Farahmandfar, Reza ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b SARI AGRICULTURAL SCIENCES AND NATURAL RESOURCES UNIVERSITY   (Iran)

^c FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

Author keywords

Adaptive neuro fuzzy inference system; Artificial neural network; Curcumin; Lipid oxidation; Sensitivity analysis; Soybean oil

Indexed keywords

FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; LINEAR REGRESSION; NEURAL NETWORKS; OIL SHALE; OXIDATION; PLANTS (BOTANY); RADIAL BASIS FUNCTION NETWORKS; SENSITIVITY ANALYSIS; TRACKING (POSITION);

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANTI-OXIDANT ACTIVITIES; CONSTRUCTION OF MODELS; CURCUMIN; LIPID OXIDATION; MULTI LAYER PERCEPTRON; MULTIPLE LINEAR REGRESSIONS; RADIAL BASIS FUNCTION(RBF);

SOYBEAN OIL;

EID: 84940005993     PISSN: 21934126     EISSN: 21934134     Source Type: Journal    
DOI: 10.1007/s11694-015-9226-7     Document Type: Article

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