干旱区生态环境知识资源中心(Arid): Advancing Agricultural Predictions: A Deep Learning Approach to Estimating Bulb Weight Using Neural Prophet Model

Arid

DOI	10.3390/agronomy13051362
	Advancing Agricultural Predictions: A Deep Learning Approach to Estimating Bulb Weight Using Neural Prophet Model
	Kim, Wonseong; Soon, Byung Min
通讯作者	Soon, BM
来源期刊	AGRONOMY-BASEL
EISSN	2073-4395
出版年	2023
卷号	13 期号:5
英文摘要	A deep learning methodology was utilized to predict the bulb weights of garlic and onions in the Jeolla Province of Korea. The Korea Rural Economic Institute (KREI) operates the Outlook & Agricultural Statistics Information System (OASIS) platform, which provides actual measurements of garlic and onions. We trained the Neural Prophet (NP) lagged time-series model using this data. The NP model effectively handles lagged variables and their covariates by inserting a hidden layer. Our results indicate that the NP model performed with around 5% mean absolute error in predicting bulb weights, with a gap of 3.3 g and 4.7 g with average weights of 63.7 g and 129.9 g for garlic and onions, respectively. This experimental research was based on only three years of measurement data. Hence, the gap between observed and predicted data can be reduced by accumulating more measurement data in the future.
英文关键词	deep learning Neural Prophet bulb weight prediction agricultural production measurement data
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000995341000001
WOS类目	Agronomy ; Plant Sciences
WOS研究方向	Agriculture ; Plant Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395207
推荐引用方式 GB/T 7714	Kim, Wonseong,Soon, Byung Min. Advancing Agricultural Predictions: A Deep Learning Approach to Estimating Bulb Weight Using Neural Prophet Model[J],2023,13(5).
APA	Kim, Wonseong,&Soon, Byung Min.(2023).Advancing Agricultural Predictions: A Deep Learning Approach to Estimating Bulb Weight Using Neural Prophet Model.AGRONOMY-BASEL,13(5).
MLA	Kim, Wonseong,et al."Advancing Agricultural Predictions: A Deep Learning Approach to Estimating Bulb Weight Using Neural Prophet Model".AGRONOMY-BASEL 13.5(2023).