Development and Verification of Smart Greenhouse Internal Temperature Prediction Model Using Machine Learning Algorithm-Reference-Cited by-同舟云学术

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Development and Verification of Smart Greenhouse Internal Temperature Prediction Model Using Machine Learning Algorithm

Published:2022-07-31 Issue:3 Volume:31 Page:152-162
ISSN:1229-4675
Container-title:Journal of Bio-Environment Control
language:en
Short-container-title:J. Bio-Env. Con.

Author:

Oh Kwang Cheol^ORCID,Kim Seok Jun¹,Park Sun Yong¹,Lee Chung Geon²,Cho La Hoon¹,Jeon Young Kwang¹,Kim Dae Hyun³

Affiliation:

1. Graduate Student, Department of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon 24341, Korea

2. Researcher, Agriculture and Life Science Research Institute, Kangwon National University, Chuncheon 24341, Korea

3. Professor, Department of Biosystems Engineering, Kangwon National University, Chuncheon 24341, Korea

Publisher

The Korean Society for Bio-Environment Control

Link

http://www.ksbec.org/articles/pdf/doi/10.12791/KSBEC.2022.31.3.152.pdf

Reference30 articles.

1. Automatic Control System for Cultivation Environment of Crops

2. Ariga M., S. Nakayama, and D. Nishibayasi 2018, Machine learning at work. O'Reilly Media, CA, USA, pp 137-140.

3. Electricity price prediction based on hybrid model of adam optimized LSTM neural network and wavelet transform

4. Charu C.A. 2018, Neural networks and deep learning: a Textbook. Springer, Heidelberg, Germany, pp 123-127.

5. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

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