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Paper Abstract and Keywords
Presentation 2018-07-11 14:00
[Encouragement Talk] Bayesian Optimization for Searching for the Optimal Climate Recipe in Completely Controlled Plant Factory
Tatsuya Iizuka, Ryo Shigeta, Yoshihiro Kawahara (Tokyo Univ.) ASN2018-24
Abstract (in Japanese) (See Japanese page) 
(in English) A data-driven method for improving the productivity in plant factories is desired. The environmental response including growth speed depends on when and how the surrounding environment is changed. Several studies have applied a machine learning method that could handle time series data such as Recurrent Neural Network to achieve an optimal environment. The key has been to construct the predictor of environmental response given the time series of past environment data as train data. However, few studies have focused on how to collect the train data. An intelligent sampling method can reduce the required size of it and time for the entire experiment. In this paper, we propose a novel sampling method of environmental data points in plant factories to achieve the optimal environment with a small number of data. Bayesian Optimization is applied to maximize the growth rate of leaf area index in our experiment.
Keyword (in Japanese) (See Japanese page) 
(in English) Vertical Farming / Bayesian Optimization / Climate Recipe / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 127, ASN2018-24, pp. 47-52, July 2018.
Paper # ASN2018-24 
Date of Issue 2018-07-04 (ASN) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF ASN2018-24

Conference Information
Committee ASN NS RCS SR RCC  
Conference Date 2018-07-11 - 2018-07-13 
Place (in Japanese) (See Japanese page) 
Place (in English) Hakodate Arena 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT（Internet of Things）, etc. 
Paper Information
Registration To ASN 
Conference Code 2018-07-ASN-NS-RCS-SR-RCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Bayesian Optimization for Searching for the Optimal Climate Recipe in Completely Controlled Plant Factory 
Sub Title (in English)  
Keyword(1) Vertical Farming  
Keyword(2) Bayesian Optimization  
Keyword(3) Climate Recipe  
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1st Author's Name Tatsuya Iizuka  
1st Author's Affiliation The University of Tokyo (Tokyo Univ.)
2nd Author's Name Ryo Shigeta  
2nd Author's Affiliation The University of Tokyo (Tokyo Univ.)
3rd Author's Name Yoshihiro Kawahara  
3rd Author's Affiliation The University of Tokyo (Tokyo Univ.)
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Speaker Author-1 
Date Time 2018-07-11 14:00:00 
Presentation Time 25 minutes 
Registration for ASN 
Paper # ASN2018-24 
Volume (vol) vol.118 
Number (no) no.127 
Page pp.47-52 
#Pages 6 
Date of Issue 2018-07-04 (ASN) 

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