• DocumentCode
    2813586
  • Title

    Authentic modeling of complex dynamics of biological systems by the manipulation of artificial intelligence

  • Author

    Falahian, Razieh ; Dastjerdi, Maryam Mehdizadeh ; Gharibzadeh, Shahriar

  • Author_Institution
    Dept. of Biomed. Eng., Amirkabir Univ. of Technol. (AUT), Tehran, Iran
  • fYear
    2015
  • fDate
    3-5 March 2015
  • Firstpage
    47
  • Lastpage
    52
  • Abstract
    The recent meteoric significant developments in the biological and medical sciences have been the culmination of substantial efforts devoted to precisely modeling the behavior of biological systems and their responses to various stimuli. The complicated interactions within varied components of biological systems as well as with their environments make them extremely complex nonlinear systems. The results of several contemporary relevant investigations have manifested their chaotic behavioral patterns. With the aim of modeling this specific behavior of bio-systems, we employ a particular multilayer feed-forward neural network. The distinctive feature of our modeling method, which makes it dominant within the modeling techniques, is training the select neural network with the chaotic map extracted from the under-study time series. Our results, which are briefly represented in this paper, confirm that the specified neural network does possess the potentiality to model the chaotic dynamics of biological systems., even in the presence of noise. In pursuance of evaluating our model, we assess and model the chaotic response of the brain to the flicker light through some recorded electroretinogram data.
  • Keywords
    artificial intelligence; chaos; electroretinography; feature extraction; medical signal processing; multilayer perceptrons; time series; artificial intelligence manipulation; biological system; chaotic dynamics; chaotic map extraction; complex dynamics modelling; complex nonlinear system; electroretinogram data; multilayer feed-forward neural network; time series; Bifurcation; Biological neural networks; Biological system modeling; Brain modeling; Chaos; Fuzzy control; Training; Artificial Neural Network; biological systems; brain; chaotic behavior; modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on
  • Conference_Location
    Mashhad
  • Print_ISBN
    978-1-4799-8817-4
  • Type

    conf

  • DOI
    10.1109/AISP.2015.7123513
  • Filename
    7123513