• Journal of information and communication convergence engineering
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• 제18권3호
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• pp.167-175
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• 2020

The net income per unit area from crop production could be the most critical consideration for agricultural producers during cultivation planning. This paper proposes a scheme for predicting the net income per unit area based on machine learning and related calculations. This scheme predicts rice production and operation costs by applying climate and price index data. The rice price is also predicted by applying rice production and operation cost data. Finally, these predicted results are employed to calculate the predicted net income, which is compared with the actual net income. Consequently, the proposed scheme shows a meaningful degree of conformity, which indicates the potential of machine learning for predicting various aspects of agricultural production.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.8-13
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• 2019

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 over-production 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 pre-production 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.

• 생물환경조절학회지
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• 제5권2호
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• pp.174-186
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• 1996

This study was carried out in order to understand the plan, design, constructing and actual condition of management of modernized horticultural facilities in Kyungpook Province which had been constructed from 1992 to 1995 funded by Government support. The aim of this study is to provide reference data for success of the forth project. It was performed by making up a question about driving of project and management condition of equipment after constructing. The results obtained from this study are as follows: 1. 73.5% of facilities horticulture farmhouse recognized that the prospect of greenhouse is bright, but 92.5% of the farmhouse also recognised that they need technical consultation on protected horticulture farming. Therefore, technical educations would must be enhanced about foundation of greenhouse and cultivation technique. 2. The holding times of explanatory meetings, cause of understanding to farmhouse, were one or two times in greenhouse construction, and 62.5% of the farmhouse expressed the insufficiency at the explanation and educational data. For this reason, it was judged that the construction contract had been delayed more than 5 months in 49.3% of the farmhouse after the decision of project budget. 3. In constructing after a contract, the rates of construction delay is 53.4% and defect occurrence is 41.1%. The biggest reasons of construction delay was insufficiency of worker and materials supply. Each percentage is 29.1%. And the reason of defect occurrence is badness of machinery equipment(62.9% ). 4. In management of greenhouse, a pipe-constructed plastic film greenhouse changes plastic film every one and three years because of sticking dust on plastic film. It was needed to about in cleaning technique of coverings. Because that used 3-5 years only half of the expected life span. 5. The order of broken rating in the subsidiary equipment is like this lollop ventilator (42.8%), a general control system(33.3%) especially, in the case of a general control system, the rate of all family can control is 52.7%. so, it is time to develop easy control equipment which every one could use as soon as possible. 6. When choose heat generator as decide capacity, the most priority is the mount of heat generator the percent is 45.5% heat generator and as decide model, the private purchase's percent is 77.3%. It is higher than a public bidding heat generator the percent is 22.7% heat generator when it compare with a public bidding. In the case of $CO_2$ generator, using rate is only 19.0%. The using rate is very low, so it needs education how to use depends on the way of the subsidiary equipment. 7. In the case of seedlings, it is asked to use factory-processed seedling effectively. because it's difficult to get security of labors(58.8%), hoped crops (55.9%) access same crops(29.4%) much more and changing of crops depends on market situation. that is the main reason the lack of knowhow.