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Volumn 50, Issue , 2011, Pages 124-128

Improving an artificial neural network model to predict thyroid bending protein diagnosis using preprocessing techniques

Author keywords

Artificial Neural Networks; Back propagation algorithm; Data pre processing; Machine learning

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; DATA PREPROCESSING; DATA PREPROCESSING TECHNIQUE; DATA SETS; DIFFERENT DOMAINS; LEARNING TECHNIQUES; MEDICAL DIAGNOSIS SYSTEM; NOISY DATA; OPERATING DATA; PREPROCESSING TECHNIQUES; TRAINING AND TESTING; TRAINING PROCESS;

EID: 84871307007     PISSN: 2010376X     EISSN: 20103778     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (3)

References (7)
  • 7
    • 40649114979 scopus 로고    scopus 로고
    • Improvement of an Artificial Neural Network Model using Min-Max Preprocessing for the Prediction of Wave-induced Seabed Liquefaction
    • Vancouver, BC, Canada
    • Deaho Cha, Michael Blumenstein, Hong Zhang, and Dong-Sheng Jeng (July, 2006), Improvement of an Artificial Neural Network Model using Min-Max Preprocessing for the Prediction of Wave-induced Seabed Liquefaction, 2006 International Joint Conference, Vancouver, BC, Canada.
    • (2006) 2006 International Joint Conference
    • Cha, D.1    Blumenstein, M.2    Zhang, H.3    Jeng, D.-S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.