Analysis of Combination of Kohonen Algorithm and Resilient Backpropagation in Weighting Process

  • Authors

    • Medina Roselia Lasmauli Tambunan
    • Poltak Sihombing
    • Pahala Sirait
    • . .
    https://doi.org/10.14419/ijet.v7i3.5.21662
  • Kohonen, Risilent Backpropagation, Kohorprop

  • Abstract

    The Kohonen algorithm is the most superior clustering algorithm in artificial neural networks compared to other clustering algorithms, and the Resilient Backpropagation (RProp) algorithm is the best algorithm in the supervised algorithm. From the results of this study, the author tries to do a research combining kohonen algorithm with RProp algorithm, where the clustering results in the kohonen algorithm will be used as the initial input process in RProp algorithm which can speed up the data processing in RProp. In this study a combination of kohonen algorithm and Resilient Backpropagation algorithm is produced, which is abbreviated as Kohorprop (Kohonen Risilient Backpropagation). From the test results, the percentage of the Kohorpor versus RProp algorithm speed with testing for 100, 500, 1,000, 5,000, 10,000 data in 10 attempts, respectively: 54.70%, 52.92%, 50.40%, 68.52%, and 78.70%. So that shows that the Kohorprop algorithm is faster than the RProp algorithm

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  • How to Cite

    Roselia Lasmauli Tambunan, M., Sihombing, P., Sirait, P., & ., . (2018). Analysis of Combination of Kohonen Algorithm and Resilient Backpropagation in Weighting Process. International Journal of Engineering & Technology, 7(3.5), 105-108. https://doi.org/10.14419/ijet.v7i3.5.21662

    Received date: 2018-11-26

    Accepted date: 2018-11-26