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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보통신학회JICCE Journal of information and communication convergence engineering Journal of information and communication convergence engineering Vol.17 No.1
- 발행연도
- 2019.3
- 수록면
- 8 - 13 (6page)
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초록· 키워드
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Smart Farming has been regarded as an important application in information and communications technology (ICT) fields. Selecting crops for cultivation at the pre-production stage is critical for agricultural producers’ final profits because overproduction and under-production may result in uncountable losses, and it is necessary to predict crop production to prevent these losses. The ITU-T Recommendation for Smart Farming (Y.4450/Y.2238) defines plan/production consultation service at the preproduction stage; this type of service must trace crop production in a predictive way. Several research papers present that machine learning technology can be applied to predict crop production after related data are learned, but these technologies have little to do with standardized ICT services. This paper clarifies the relationship between agricultural consultation services and predicting crop production. A prediction scheme is proposed, and the results confirm the usability and superiority of machine learning for predicting crop production.
목차
Abstract
I. INTRODUCTION
II. FRAMEWORK OF AGRICULTURAL CONSULTATIONSERVICE
III. PROPOSED PREDICTION SCHEME
IV. DISCUSSION AND CONCLUSIONS
REFERENCES
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