Home-legacy device intelligent control using ANFIS with data regeneration and resampling

Junho Chung, In Hwan Choi, Sung Hyun Yoo, Myo Taeg Lim, Hyun Kook Lee, Moon Kyu Song, Choon Ki Ahn

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

Abstract

In recent years, the research for electric power usage reduction in a house has been widely studied. Home energy management system (HEMS) is become one of major applications to handle many smart electrical devices inside house that proves its electricity usage reduction efficiently. However, HEMS has a critical issue which cannot control non-smart devices at home. Saving unnecessary energy usage for legacy devices remains research area to prevent from expansions of energy waste for users. In this paper, an intelligence inference control approach based on the adaptive neural-fuzzy inference system (ANFIS) is proposed for legacy devices. The approach based on ANFIS focuses to reduce computation of training time by performing regeneration and resampling approach compared to conventional ANFIS.

Original languageEnglish
Title of host publicationICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1294-1296
Number of pages3
ISBN (Print)9788993215090
DOIs
Publication statusPublished - 2015 Dec 23
Event15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of
Duration: 2015 Oct 132015 Oct 16

Other

Other15th International Conference on Control, Automation and Systems, ICCAS 2015
CountryKorea, Republic of
CityBusan
Period15/10/1315/10/16

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Keywords

  • Artificial neural fuzzy inference system (ANFIS)
  • Home energy management system (HEMS)
  • Legacy device
  • Regeneration
  • Resampling

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Chung, J., Choi, I. H., Yoo, S. H., Lim, M. T., Lee, H. K., Song, M. K., & Ahn, C. K. (2015). Home-legacy device intelligent control using ANFIS with data regeneration and resampling. In ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings (pp. 1294-1296). [7364836] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAS.2015.7364836