Comparison of adaptive neuro-fuzzy inference system and artificial neural networks for estimation of oxidation parameters of sunflower oil added with some natural byproduct extracts

Journal of the Science of Food and Agriculture

Volumn 92, Issue 1, 2012, Pages 49-58

  Karaman, Safa ^a   Ozturk, Ismet ^a   Yalcin, Hasan ^a   Kayacier, Ahmed ^a   Sagdic, Osman ^a  

^a ERCIYES UNIVERSITY   (Turkey)

Author keywords

ANFIS; ANN; Antioxidant; Byproduct; Modeling; Oxidation; Refined sunflower oil

Indexed keywords

ANTIOXIDANT; PEROXIDE; PLANT EXTRACT; SUNFLOWER OIL; VEGETABLE OIL;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; CHEMISTRY; COMPARATIVE STUDY; FOOD PRESERVATION; FOOD STORAGE; FRUIT; FUZZY LOGIC; HUMAN; MALUS; METABOLISM; METHODOLOGY; OXIDATION REDUCTION REACTION; PLANT TUBER; POTATO; STATISTICAL MODEL; SUNFLOWER; SWEET ORANGE;

ANTIOXIDANTS; CITRUS SINENSIS; FOOD PRESERVATION; FOOD STORAGE; FRUIT; FUZZY LOGIC; HELIANTHUS; HUMANS; LINEAR MODELS; MALUS; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); OXIDATION-REDUCTION; PEROXIDES; PLANT EXTRACTS; PLANT OILS; PLANT TUBERS; SOLANUM TUBEROSUM;

HELIANTHUS; MALUS X DOMESTICA; SOLANUM TUBEROSUM;

EID: 82855165145     PISSN: 00225142     EISSN: 10970010     Source Type: Journal    
DOI: 10.1002/jsfa.4540     Document Type: Article

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