Tobacco yield estimation via multi-source data fusion and recurrent neural networks

In China, tobacco production must strictly follow the yield plan set by the higher authorities. In this context, accurate and stable yield estimation is meaningful for effective production management. In this paper, we adopted a multi-source data fusion strategy to develop the yield estimation model...

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Vydané v:	International journal of applied earth observation and geoinformation Ročník 144; s. 104925
Hlavní autori:	Zhang, Mingzheng, Zhang, Baoyuan, Zhao, Chunjiang, Chen, Liping, Kuai, Yan, Wang, Cong, Jiang, Shuwen, Chen, Dong, Zhu, Qingzhen, Wang, Zhiyong, Gu, Xiaohe, Chen, Tian’en
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.11.2025 Elsevier
Predmet:	AEC1D HF+BCP+BPP Multi-source data fusion RNN Yield estimation RNN Yield estimation HF+BCP+BPP AEC1D Multi-source data fusion
ISSN:	1569-8432
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