Hyperbolic tangent activation function on FIMT-DD algorithm analysis for airline big data

Ari Wibisono, Machmud Roby Alhamidi, Adi Nurhadiyatna, Wisnu Jatmiko

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

1 Citation (Scopus)

Abstract

In recent years, big data has become hot and challenging issue. The use of big data term in many areas provided positive impact. In traffic area included road traffic, railway traffic, and airline traffic, there is huge information can be obtained. The needed of big data analytics to process the data quickly and give an accurate prediction about it, became essential. The FIMT-DD with hyperbolic tangent (tanh) algorithm is proposed to predict the airline big data. The simulation time of FIMT-DD-tanh is almost the same with original FIMT-DD. Based on this analysis and evaluation, in data stream mining evaluation, FIMT-DD-tanh could be able to decrease the error value in airline big dataset.

Original languageEnglish
Title of host publicationProceedings - WBIS 2017
Subtitle of host publication2017 International Workshop on Big Data and Information Security
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages31-36
Number of pages6
ISBN (Electronic)9781538620380
DOIs
Publication statusPublished - 29 Jan 2018
Event2017 International Workshop on Big Data and Information Security, WBIS 2017 - Jakarta, Indonesia
Duration: 23 Sep 201724 Sep 2017

Publication series

NameProceedings - WBIS 2017: 2017 International Workshop on Big Data and Information Security
Volume2018-January

Conference

Conference2017 International Workshop on Big Data and Information Security, WBIS 2017
CountryIndonesia
CityJakarta
Period23/09/1724/09/17

Keywords

  • Activation Function
  • Airline data
  • Big Data
  • FIMT-DD
  • Hyperbolic Tangent

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    Wibisono, A., Alhamidi, M. R., Nurhadiyatna, A., & Jatmiko, W. (2018). Hyperbolic tangent activation function on FIMT-DD algorithm analysis for airline big data. In Proceedings - WBIS 2017: 2017 International Workshop on Big Data and Information Security (pp. 31-36). (Proceedings - WBIS 2017: 2017 International Workshop on Big Data and Information Security; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWBIS.2017.8275099