Impact of small-world network topology on the conventional artificial neural network for the diagnosis of diabetes

Chaos, Solitons and Fractals

Volumn 83, Issue , 2016, Pages 178-185

  Erkaymaz, Okan ^a   Ozer, Mahmut ^a  

^a ZONGULDAK KARAELMAS UNIVERSITY   (Turkey)

Author keywords

Diabetic; Feed forward artificial neural network; Small world network

Indexed keywords

ARTIFICIAL INTELLIGENCE; DIAGNOSIS; INTELLIGENT SYSTEMS; NEURAL NETWORKS;

ACCURACY ANALYSIS; ARTIFICIAL INTELLIGENT; CLASSIFICATION PERFORMANCE; CLASSIFIER PERFORMANCE; DIABETIC; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; NEW APPROACHES; OUTPUT ERRORS;

SMALL-WORLD NETWORKS;

EID: 84952324262     PISSN: 09600779     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chaos.2015.11.029     Document Type: Article

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