Vassilis S Kodogiannis

Summary

Affiliation: University of Westminster
Country: UK

Publications

  1. ncbi request reprint The use of gas-sensor arrays to diagnose urinary tract infections
    Vassilis Kodogiannis
    Mechatronics Group, School of Computer Science, University of Westminster, London, UK
    Int J Neural Syst 15:363-76. 2005
  2. doi request reprint Artificial odor discrimination system using electronic nose and neural networks for the identification of urinary tract infection
    Vassilis S Kodogiannis
    Centre for Systems Analysis, School of Computer Science, University of Westminster, London HA1 3TP, UK
    IEEE Trans Inf Technol Biomed 12:707-13. 2008
  3. doi request reprint A clustering-based fuzzy wavelet neural network model for short-term load forecasting
    Vassilis S Kodogiannis
    School of Electronics and Computer Science, University of Westminster, 115 New Cavendish Street, London W1W 6UW, UK
    Int J Neural Syst 23:1350024. 2013

Detail Information

Publications3

  1. ncbi request reprint The use of gas-sensor arrays to diagnose urinary tract infections
    Vassilis Kodogiannis
    Mechatronics Group, School of Computer Science, University of Westminster, London, UK
    Int J Neural Syst 15:363-76. 2005
    ..This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology...
  2. doi request reprint Artificial odor discrimination system using electronic nose and neural networks for the identification of urinary tract infection
    Vassilis S Kodogiannis
    Centre for Systems Analysis, School of Computer Science, University of Westminster, London HA1 3TP, UK
    IEEE Trans Inf Technol Biomed 12:707-13. 2008
    ..This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology...
  3. doi request reprint A clustering-based fuzzy wavelet neural network model for short-term load forecasting
    Vassilis S Kodogiannis
    School of Electronics and Computer Science, University of Westminster, 115 New Cavendish Street, London W1W 6UW, UK
    Int J Neural Syst 23:1350024. 2013
    ..The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models. ..