Výsledky vyhledávání - "Myung Hwan Na"

Akademický článek

Prediction of Live Bulb Weight for Field Vegetables Using Functional Regression Models and Machine Learning Methods

Autor: Dahyun Kim, Wanhyun Cho, Inseop Na, Myung Hwan Na

Publikováno v: Agriculture, Vol 14, Iss 5, p 754 (2024)

(1) Background: This challenge is exacerbated by the aging of the rural population, leading to a scarcity of available manpower. To address this issue, the automation and mechanization of outdoor vegetable cultivation are imperative. Therefore, devel

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Akademický článek

The Development of a Weight Prediction System for Pigs Using Raspberry Pi

Autor: Myung Hwan Na, Wan Hyun Cho, Sang Kyoon Kim, In Seop Na

Publikováno v: Agriculture, Vol 13, Iss 10, p 2027 (2023)

Generally, measuring the weight of livestock is difficult; it is time consuming, inconvenient, and stressful for both livestock farms and livestock to be measured. Therefore, these problems must be resolved to boost convenience and reduce economic co

Externí odkaz: https://doaj.org/article/bffc947c448b4364a326feb4701d2d7d

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Akademický článek

Comparative Analysis of Statistical Regression Models for Prediction of Live Weight of Korean Cattle during Growth

Autor: Myung Hwan Na, Wanhyun Cho, Sora Kang, Inseop Na

Publikováno v: Agriculture, Vol 13, Iss 10, p 1895 (2023)

Measuring weight during cattle growth is essential for determining their status and adjusting the feed amount. Cattle must be weighed on a scale, which is laborious and stressful and could hinder growth. Therefore, automatically predicting cattle wei

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Akademický článek

A Smart Farm DNN Survival Model Considering Tomato Farm Effect

Autor: Jihun Kim, Il Do Ha, Sookhee Kwon, Ikhoon Jang, Myung Hwan Na

Publikováno v: Agriculture, Vol 13, Iss 9, p 1782 (2023)

Recently, smart farming research based on artificial intelligence (AI) has been widely applied in the field of agriculture to improve crop cultivation and management. Predicting the harvest time (time-to-harvest) of crops is important in smart farmin

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Akademický článek

Prediction of Weights during Growth Stages of Onion Using Agricultural Data Analysis Method

Autor: Wanhyun Cho, Myung Hwan Na, Yuha Park, Deok Hyeon Kim, Yongbeen Cho

Publikováno v: Applied Sciences, Vol 10, Iss 6, p 2094 (2020)

In this study, we propose a new agricultural data analysis method that can predict the weight during the growth stages of the field onion using a functional regression model. We have used onion weight on growth stages as the response variable and six

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