2019년 추계 학술대회
Current Result Document :
| 한글제목(Korean Title) |
Predicting Daily Nutrient Water Consumption by Strawberry Plants in a Greenhouse Environment |
| 영문제목(English Title) |
Predicting Daily Nutrient Water Consumption by Strawberry Plants in a Greenhouse Environment |
| 저자(Author) |
Sathishkumar V E
Myeong-Bae Lee
Jong-Hyun Lim
Chang-Sun Shin
Chang-Woo Park
Yong Yun Cho
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| 원문수록처(Citation) |
VOL 26 NO. 02 PP. 0581 ~ 0584 (2019. 11) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Food consumption is growing worldwide every year owing to a growing population. Hence, the increasing population needs the production of sufficient and good quality food products. Strawberry is one of the world's most famous fruit. To obtain the highest strawberry output, we worked with three strawberry varieties supplied with three kinds of nutrient water in a greenhouse and with the outcome of the strawberry production, the highest yielding strawberry variety is detected. This Study uses the nutrient water consumed every day by the highest yielding strawberry variety. The atmospheric temperature, humidity and CO2 levels within the greenhouse are identified and used for the prediction, since the water consumption by any plant depends primarily on weather conditions. Machine learning techniques show successful outcomes in a multitude of issues including time series and regression issues. In this study, daily nutrient water consumption of strawberry plants is predicted using machine learning algorithms is proposed. Four Machine learning algorithms are used such as Linear Regression (LR), K nearest neighbour (KNN), Support Vector Machine with Radial Kernel (SVM) and Gradient Boosting Machine (GBM). Gradient Boosting System produces the best results.
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