• DocumentCode
    2466894
  • Title

    A Modular Neural Network Simulation System for Teaching/Research Based on .NET Framework

  • Author

    Feng, Shuai ; Wang, Pan

  • Author_Institution
    Wuhan Univ. of Technol., Wuhan
  • fYear
    2007
  • fDate
    23-25 Nov. 2007
  • Firstpage
    422
  • Lastpage
    427
  • Abstract
    Modular neural network is a learning paradigm where a collection of neural networks are jointly used for solving a problem. In this work ire develop a modular neural network simulation system based on .NET framework, applying a new training method named expert in one thing and good at many in constructing modular neural network. This method divides the training set into a certain number of subsets, each of which can be selected to train individual sub-network with different performance criterion. An empirical study demonstrates that the proposed method obtains significant generalization ability. In the though of Object-Oriented Programming, the simulation system ire have developed based on .NET framework provides a powerful neurocomputing functions and convenient graphical user interface to aid the study of the knowledge of modular neural network.
  • Keywords
    graphical user interfaces; learning (artificial intelligence); neural nets; object-oriented programming; teaching; .NET framework; graphical user interface; individual subnetwork training; modular neural network simulation system; neurocomputing function; object-oriented programming; teaching-research; Application software; Automation; Clustering algorithms; Computer science education; Instruments; Management training; Multi-layer neural network; Neural networks; Object oriented modeling; Object oriented programming; Data Clustering; Modularity; Neural Network; Simulation System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technologies and Applications in Education, 2007. ISITAE '07. First IEEE International Symposium on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-1386-7
  • Electronic_ISBN
    978-1-4244-1386-7
  • Type

    conf

  • DOI
    10.1109/ISITAE.2007.4409317
  • Filename
    4409317