干旱区生态环境知识资源中心(Arid): Artificial intelligence to predict soil temperatures by development of novel model

Arid

DOI	10.1038/s41598-024-60549-x
	Artificial intelligence to predict soil temperatures by development of novel model
	Mampitiya, Lakindu; Rozumbetov, Kenjabek; Rathnayake, Namal; Erkudov, Valery; Esimbetov, Adilbay; Arachchi, Shanika; Kantamaneni, Komali; Hoshino, Yukinobu; Rathnayake, Upaka
通讯作者	Rathnayake, U
来源期刊	SCIENTIFIC REPORTS
ISSN	2045-2322
出版年	2024
卷号	14 期号:1
英文摘要	Soil temperatures at both surface and various depths are important in changing environments to understand the biological, chemical, and physical properties of soil. This is essential in reaching food sustainability. However, most of the developing regions across the globe face difficulty in establishing solid data measurements and records due to poor instrumentation and many other unavoidable reasons such as natural disasters like droughts, floods, and cyclones. Therefore, an accurate prediction model would fix these difficulties. Uzbekistan is one of the countries that is concerned about climate change due to its arid climate. Therefore, for the first time, this research presents an integrated model to predict soil temperature levels at the surface and 10 cm depth based on climatic factors in Nukus, Uzbekistan. Eight machine learning models were trained in order to understand the best-performing model based on widely used performance indicators. Long Short-Term Memory (LSTM) model performed in accurate predictions of soil temperature levels at 10 cm depth. More importantly, the models developed here can predict temperature levels at 10 cm depth with the measured climatic data and predicted surface soil temperature levels. The model can predict soil temperature at 10 cm depth without any ground soil temperature measurements. The developed model can be effectively used in planning applications in reaching sustainability in food production in arid areas like Nukus, Uzbekistan.
英文关键词	Artificial intelligence Climatic parameters Machine learning Prediction Soil temperature Uzbekistan
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:001225890200040
WOS关键词	BLUE PHASE ; LIQUID-CRYSTAL ; STABILIZATION ; ISOMERIZATION
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405586
推荐引用方式 GB/T 7714	Mampitiya, Lakindu,Rozumbetov, Kenjabek,Rathnayake, Namal,et al. Artificial intelligence to predict soil temperatures by development of novel model[J],2024,14(1).
APA	Mampitiya, Lakindu.,Rozumbetov, Kenjabek.,Rathnayake, Namal.,Erkudov, Valery.,Esimbetov, Adilbay.,...&Rathnayake, Upaka.(2024).Artificial intelligence to predict soil temperatures by development of novel model.SCIENTIFIC REPORTS,14(1).
MLA	Mampitiya, Lakindu,et al."Artificial intelligence to predict soil temperatures by development of novel model".SCIENTIFIC REPORTS 14.1(2024).