Výsledky vyhledávání - "Chung-Geon Lee"

Akademický článek

Prediction Model for the Internal Temperature of a Greenhouse with a Water-to-Water Heat Pump Using a Pellet Boiler as a Heat Source Using Building Energy Simulation

Autor: Chung-Geon Lee, La-Hoon Cho, Seok-Jun Kim, Sun-Yong Park, Dae-Hyun Kim

Publikováno v: Energies, Vol 15, Iss 15, p 5677 (2022)

Although smart farms are considered an alternative to traditional agriculture, they require large amounts of energy and high investment costs, hindering their efficient implementation. In the Republic of Korea, the energy supply is primarily for heat

Externí odkaz: https://doaj.org/article/576d8c94ec5344359d4e1b3d26857f7e

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Akademický článek

Comparative Analysis of Combined Heating Systems Involving the Use of Renewable Energy for Greenhouse Heating

Autor: Chung-Geon Lee, La-Hoon Cho, Seok-Jun Kim, Sun-Yong Park, Dae-Hyun Kim

Publikováno v: Energies, Vol 14, Iss 20, p 6603 (2021)

The continued use of fossil fuels is contributing to severe environmental pollution and the establishment of an abnormal climate; consequently, alternative renewable energy sources are being actively investigated worldwide. Further, following global

Externí odkaz: https://doaj.org/article/c42e4d41baab4378bc0e5c355a45204c

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Akademický článek

Development and Validation of Mass Reduction Prediction Model and Analysis of Fuel Properties for Agro-Byproduct Torrefaction

Autor: Seok-Jun Kim, Kwang-Cheol Oh, Sun-Yong Park, Young-Min Ju, La-Hoon Cho, Chung-Geon Lee, Min-Jun Kim, In-Seon Jeong, Dae-Hyun Kim

Publikováno v: Energies, Vol 14, Iss 19, p 6125 (2021)

Global warming is accelerating due to the increase in greenhouse gas emissions. Accordingly, research on the use of biomass as energy sources, is being actively conducted worldwide to reduce CO2 emissions. Although the production of agro-byproducts i

Externí odkaz: https://doaj.org/article/6ddc73966e094edfb3afcdbbaa189984

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Akademický článek

Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model

Autor: Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

Publikováno v: Agronomy, Vol 14, Iss 11, p 2545 (2024)

We developed an internal environment prediction model for smart greenhouses using machine learning models. Machine learning models were developed by finding certain rules based on the data obtained from the target system and have the advantage of lea

Externí odkaz: https://doaj.org/article/8a9ac40ed47b4ceaa12b02dab62fdff0

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