Extreme learning machine and back propagation neural network comparison for temperature and humidity control of oyster mushroom based on microcontroller

G. M. Fuady, A. H. Turoobi, M. N. Majdi, M. Syaiin, R. Y. Adhitya, Isa Rachman, F. Rachman, M. A.P. Negara, A. Soeprijanto, R. T. Soelistijono

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

This paper presents design and experimental studies of Extreme Learning Machine (ELM) to control temperature and humidity of oyster mushroom farm house. The ideal temperature to optimize the growth of oyster mushroom in low lying areas is for about 28° Celsius and 80% of humidity, while the current method for controlling temperature and humidity is done by conventional manner using manual sprayer. Given these problems, a Single Layer Feed Forward Neural Network (SLFN's) with modification of H inverse matrix versus target matrix or also known as ELM can control the temperature and humidity of oyster mushroom farm house more faster and effectively than previous research. DHT11 sensor is used to read the temperature and humidity value. Exhaust fan and mist maker are used for conditioning the control variables. Several beginning conditions were built to compare ELM with previous methods such back propagation neural network and zero order FLC in term to find the suitable methodfor this problem.

Original languageEnglish
Title of host publication2017 International Symposium on Electronics and Smart Devices, ISESD 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages46-50
Number of pages5
ISBN (Electronic)9781538627785
DOIs
Publication statusPublished - 1 Jul 2017
Event2nd International Symposium on Electronics and Smart Devices, ISESD 2017 - Yogyakarta, Indonesia
Duration: 17 Oct 201719 Oct 2017

Publication series

Name2017 International Symposium on Electronics and Smart Devices, ISESD 2017
Volume2018-January

Conference

Conference2nd International Symposium on Electronics and Smart Devices, ISESD 2017
Country/TerritoryIndonesia
CityYogyakarta
Period17/10/1719/10/17

Keywords

  • DHT11
  • Extreme Learning Machine
  • Intel Galileo
  • Oyster Mushroom

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