Hasil Pencarian - Xingli Mao

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  1. 1
    Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements

    Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of s... oleh Siwatt Pongpiachan, Qiyuan Wang, Ronbanchob Apiratikul, Danai Tipmanee, Li Li, Li Xing, Xingli Mao, Guohui Li, Yongming Han, Junji Cao, Vanisa Surapipith, Aekkapol Aekakkararungroj, Saran Poshyachinda

    Diterbitkan 2024-01-01
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  2. 2
    Correction: Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

    Correction: Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluc... oleh Siwatt Pongpiachan, Qiyuan Wang, Ronbanchob Apiratikul, Danai Tipmanee, Li Li, Li Xing, Xingli Mao, Guohui Li, Yongming Han, Junji Cao, Vanisa Surapipith, Aekkapol Aekakkararungroj, Saran Poshyachinda

    Diterbitkan 2024-01-01
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  3. 3
    Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

    Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of s... oleh Siwatt Pongpiachan, Qiyuan Wang, Ronbanchob Apiratikul, Danai Tipmanee, Li Li, Li Xing, Xingli Mao, Guohui Li, Yongming Han, Junji Cao, Vanisa Surapipith, Aekkapol Aekakkararungroj, Saran Poshyachinda

    Diterbitkan 2024-01-01
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    Artikel
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