Daily soil moisture prediction during winter wheat growth season using an SCSSA-CNN-BiLSTM model

【Objective】Accurate prediction of field soil moisture is crucial for managing agricultural production and water-saving irrigation. This paper proposes a new method to predict soil moisture changes.【Method】The hybrid deep learning model, SCSSA-CNN-BiLSTM, was integrated with Sine Cosine Cauchy Sparro...

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Auteurs principaux:	CUI Song, WU Jin, ZHANG Naifeng, LIU Meng, HU Yongsheng, HE Yanan, GU Yue, LONG Xinya, WANG Zhenlong
Format:	Artigo
Langue:	Chinês
Publié:	Science Press 2025-08-01
Collection:	Guan'gai paishui xuebao
Sujets:	neural network; sparrow optimization algorithm; soil moisture prediction; winter wheat
Accès en ligne:	https://www.ggpsxb.com/jgpxxben/ch/reader/view_abstract.aspx?file_no=20250801&flag=1
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