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Yao Cai

Biographic Data

ID7516572
NAMEYao Cai
GIVEN NAMESYao
FAMILY NAMECai
SIGNATURECAI Y
AFFILIATIONSSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou)
ORCID0000-0003-0555-5745
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
AUTHOR COUNT2
EDITOR COUNT0
FIRST PUBLICATION YEAR2013
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Ensemble seasonal forecasting of typhoon frequency over the western North Pacific using multiple machine learning algorithms

    Open Access•Zhixiang Xiao, Ziqian Wang et al.•ARTICLE•Environmental Research Letters•2024

    This study introduces an ensemble prediction methodology employing multiple machine learning algorithms for forecasting the frequency of typhoons (TYFs) over the western North Pacific (WNP) during June‒November. Potential predictors were initially identified based on the relationships between the year-by-year variation (DY) of the TYFs and preseason (March–May) environmental factors. These predictors were subsequently further refined, resulting i…

  • Palaeoclimate reconstruction based on pollen records from the Tangke and Riganqiao peat sections in the Zoige Plateau, China

    Open Access•Chun-xiao Guo, Fan Luo et al.•ARTICLE•Quaternary International•2013

No prominent works on this page.

  • Palaeoclimate reconstruction based on pollen records from the Tangke and Riganqiao peat sections in the Zoige Plateau, China

    Open Access•Chun-xiao Guo, Fan Luo et al.•ARTICLE•Quaternary International•2013

  • Ensemble seasonal forecasting of typhoon frequency over the western North Pacific using multiple machine learning algorithms

    Open Access•Zhixiang Xiao, Ziqian Wang et al.•ARTICLE•Environmental Research Letters•2024

    This study introduces an ensemble prediction methodology employing multiple machine learning algorithms for forecasting the frequency of typhoons (TYFs) over the western North Pacific (WNP) during June‒November. Potential predictors were initially identified based on the relationships between the year-by-year variation (DY) of the TYFs and preseason (March–May) environmental factors. These predictors were subsequently further refined, resulting i…

Climatology (2 works) · Environmental Science (2 works) · Geography (2 works) · Geology (2 works) · Algorithm (1 works) · Archaeology (1 works) · Artificial Intelligence (1 works) · Climate change (1 works) · Climate variability and models (1 works) · Coastal wetland ecosystem dynamics (1 works)

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