On the parallelization and optimization of the genetic-based ANN classifier for the diagnosis of students with learning disabilities

Tung-Kuang Wu, Shian-Chang Huang, Y. L. Lin, H. Chang, Y. R. Meng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Diagnosis of students with learning disabilities has long been a difficult issue as it requires extensive man power and takes a long time. Through genetic algorithm based feature selection method and genetic based parameters optimization, artificial neural network (ANN) classifier has proven to be a good predictor to the diagnosis of students with learning disabilities. In this study, we keep focusing on the ANN model and compare three strategies of parallelizing the ANN parameter optimization procedure with OpenMP and MPI APIs. Not surprisingly, the outcomes show that all three parameter optimization procedures indeed converged or executed more quickly with the aid of parallel processing. In particular, the genetic-based method tends to derive the best accuracy and require less execution time. Most important of all, potentially due to a more diverse search space provided by the distributed parallel processing environment, the accuracy of the genetic-based ANN classifier may also be improved in general. In addition, with appropriate combinations of features and parameters setting, the accuracy in LD identification model has exceeded the 90% mark (using 5-fold cross validation), which is the best we have achieved so far. The result suggests that genetic-based (or perhaps similar) optimization methods may be benefited, both in reducing execution time and achieving better outcome, from current grid-based computing technologies.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages4263-4269
Number of pages7
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey
Duration: 2010 Oct 102010 Oct 13

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Other

Other2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
CountryTurkey
CityIstanbul
Period10-10-1010-10-13

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

Cite this

Wu, T-K., Huang, S-C., Lin, Y. L., Chang, H., & Meng, Y. R. (2010). On the parallelization and optimization of the genetic-based ANN classifier for the diagnosis of students with learning disabilities. In 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 (pp. 4263-4269). [5642486] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2010.5642486