Research on the prediction models of forest fuel moisture content based on meteorological factors

YUAN Xiaoyu1; YANG Xiaodan1*; WANG Zhongyu2

doi:10.3981/j.issn.1000-7857.2023.16.011

YUAN Xiaoyu1, YANG Xiaodan1*, WANG Zhongyu2

Science & Technology Review ›› 2023, Vol. 41 ›› Issue (16) : 124-135.

PDF(4759 KB)

Science & Technology Review ›› 2023, Vol. 41 ›› Issue (16) : 124-135. DOI: 10.3981/j.issn.1000-7857.2023.16.011

Papers

Research on the prediction models of forest fuel moisture content based on meteorological factors

{{article.zuoZhe_EN}}

Author information -

About authors:

Corresponding authors:

HeighLight

Abstract

Key words

QR code of this article

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2023, 41(16): 124-135 https://doi.org/10.3981/j.issn.1000-7857.2023.16.011

References

List( Publishing order | Descend order by publishing year | Descend order by cited within ) Chart analysis

References

Funding

RIGHTS & PERMISSIONS

PDF(4759 KB)

Accesses

Citation

Detail

Sections

Recommended

Please choose a citation manager

Content to export