SNUEI

Forecasting Root-Zone Electrical Conductivity of Nutrient Solutions in Closed-Loop Soilless Cultures via a Recurrent Neural Network Using Environmental and Cultivation Information

2018 · Frontiers in Plant Science

저자

Taewon Moon, 안태인 (Tae In Ahn), Jung Eek Son

연구주제

Innovations in Aquaponics and Hydroponics Systems

NTIS 과학기술표준분류

에너지/자원만에너지·환경·원자력 확장

가장 가까운 분류(농림수산식품 > 원예특용작물과학 > 원예특용작물 시설/재배)가 에너지·환경·원자력 확장 범위 밖이다.

AI 연구 키워드·방법

순환식 양액재배 root zone electrical conductivity 파프리카(단고추)

딥러닝

키워드 (OpenAlex)

nutrient solution management hydroponics recurrent neural networks long short-term memory sweet pepper Capsicum annuum greenhouse cultivation environmental factors

초록

In existing closed-loop soilless cultures, nutrient solutions are controlled by the electrical conductivity (EC) of the solution. However, the EC of nutrient solutions is affected by both growth environments and crop growth, so it is hard to predict the EC of nutrient solution. The objective of this study was to predict the EC of root-zone nutrient solutions in closed-loop soilless cultures using recurrent neural network (RNN). In a test greenhouse with sweet peppers (Capsicum annuum L.), data were measured every 10 seconds from October 15 to December 31, 2014. Mean values for every hour were analyzed. Validation accuracy (R2) of a single-layer long short-term memory (LSTM) was 0.92 and root mean square error (RMSE) was 0.07, which were the best results among the different RNNs. The trained LSTM predicted the substrate EC accurately at all ranges. Test accuracy (R2) was 0.72 and RMSE was…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

이 문서와 연결된 페이지

교수 1

안태인

연구주제 1

Innovations in Aquaponics and Hydroponics Systems

키워드 2

순환식 양액재배 · 파프리카(단고추)

방법 1

딥러닝