Machine Learning For Temperature Forecasting

Machine Learning for Temperature Forecasting is a computational methodology that employs data-driven algorithms to model and predict temperature variations over time and space by learning patterns from historical meteorological data.

465

Publications

21.8K

Citations

1.6K

Authors

701

Institutions

Publications per year

2017–2026

344

Authors

1.6K

  1. ÖK
    Özgür Kişi

    Ilia State University, Georgia

    8 publications · 332 citations

    8

    h-index

  2. SK
    Sungwon Kim

    Dongyang University, South Korea

    6 publications · 171 citations

    6

    h-index

  3. SS
    Shahaboddin Shamshirband

    University of Malaya, Malaysia

    6 publications · 500 citations

    6

    h-index

  4. RW
    R. W. McClendon

    University of Georgia, United States

    5 publications · 493 citations

    5

    h-index

  5. ZM
    Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

    Ton Duc Thang University, Vietnam

    5 publications · 305 citations

    5

    h-index

1–5 of 1.6K

Venues

  1. Energy and Buildings

    12 publications · 929 citations

    13

    h-index

  2. Sensors

    13 publications · 449 citations

    13

    h-index

  3. Scientific Reports

    6 publications · 145 citations

    9

    h-index

  4. Applied Thermal Engineering

    7 publications · 363 citations

    8

    h-index

  5. Computers and Electronics in Agriculture

    8 publications · 523 citations

    8

    h-index

1–5