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The Experts below are selected from a list of 69 Experts worldwide ranked by ideXlab platform

Azmi Zakaria - One of the best experts on this subject based on the ideXlab platform.

  • application of beta distribution model to malaysian Sunshine Data
    Renewable Energy, 1999
    Co-Authors: Yusof M Sulaiman, Mahdi Abd Wahab, Azmi Zakaria
    Abstract:

    Abstract Malaysian Sunshine Data covering a ten-year period were fitted to a beta distribution model. Most of the months follow mount shape distributions. The K–S statistics indicated that the distributions fitted well the Petaling Jaya and Subang stations. All months could not be rejected at 5% level. For the Bayan Lepas and Kota Bharu stations, some months were significantly different. Our Data showed a weak empirical relationship between the mean and standard deviation and this rules out the possibility of using tabulated mean Sunshine Data to estimate the standard deviation. The standard deviation must therefore be calculated from the measured Data. For Malaysia, measured daily Sunshine Data must be made available before the model can be used.

  • application of probability models to malaysian Sunshine Data
    International Journal of Energy Research, 1998
    Co-Authors: Yusof M Sulaiman, Mahdi Abd Wahab, Azmi Zakaria
    Abstract:

    A 10-year Malaysian Sunshine Data of four stations were fitted to three models, namely the Bendt, Hollands and Huget and Saunier models. Distribution parameters of the models were determined from the values of the observed mean of the Sunshine Data. The Kolmogorov–Smirnov test was applied to determine the goodness of fit. It was found that the Saunier model was suitable for the Petaling Jaya and Subang stations while the Hollands and Huget model well suited the Bayan Lepas and Kota Bharu stations. The Bendt model did not give a good fit for all stations. It was also found that for the months that have the same observed mean but different observed standard deviations the distribution models were able to fit well only if the estimated standard deviations were close in value to the observed standard deviations.

A.a. Trabea - One of the best experts on this subject based on the ideXlab platform.

  • Technical note a multiple linear correlation for diffuse radiation from global solar radiation and Sunshine Data over Egypt
    Renewable Energy, 1999
    Co-Authors: A.a. Trabea
    Abstract:

    Measurements of global solar radiation, diffuse radiation and Sunshine duration Data during the period from 1982 to 1988 at different locations over Egypt were used to establish empirical relationships that would connect the daily monthly average diffuse irradiation with both relative Sunshine duration and clearness index separately and in combination. The selected locations were chosen to represent the different weather conditions of North, Middle and South Egypt. Our correlation equations were tested using measured Data for the year 1992 at the same locations. The correlation connecting diffuse radiation with both clearness index and percentage possible Sunshine is found to be applicable over Egypt.

P Yianoulis - One of the best experts on this subject based on the ideXlab platform.

  • study of the weather from Sunshine Data
    Renewable Energy, 1993
    Co-Authors: K Zabara, P Yianoulis
    Abstract:

    Of considerable interest to solar energy applications is the sequence of days of “good” or “bad” weather. In this work we study the dependence of the weather on that of the 2 days before, based on Sunshine Data for a period of 30 years. The results show that this varies considerably during the year and is a function of the daily relative Sunshine (DRS). We also present the generation of sequence of k consecutive days during which the DRS is greater or less (“good” or “bad” weather) than a value x(0 < x < 1).

  • conditional probabilities of daily relative Sunshine Data and the dependence on the weather of the previous day
    Solar Energy, 1992
    Co-Authors: K Zabara, P Yianoulis
    Abstract:

    Abstract In this paper, the conditional probabilities p11(m, x) and p01(m, x) of the daily relative Sunshine (DRS) are estimated for each month m, using available Data for 30 years. p11(m, x) (p01(m, x)) is the probability that the DRS of a day for a certain month is greater than x, (o

Yusof M Sulaiman - One of the best experts on this subject based on the ideXlab platform.

  • application of beta distribution model to malaysian Sunshine Data
    Renewable Energy, 1999
    Co-Authors: Yusof M Sulaiman, Mahdi Abd Wahab, Azmi Zakaria
    Abstract:

    Abstract Malaysian Sunshine Data covering a ten-year period were fitted to a beta distribution model. Most of the months follow mount shape distributions. The K–S statistics indicated that the distributions fitted well the Petaling Jaya and Subang stations. All months could not be rejected at 5% level. For the Bayan Lepas and Kota Bharu stations, some months were significantly different. Our Data showed a weak empirical relationship between the mean and standard deviation and this rules out the possibility of using tabulated mean Sunshine Data to estimate the standard deviation. The standard deviation must therefore be calculated from the measured Data. For Malaysia, measured daily Sunshine Data must be made available before the model can be used.

  • application of probability models to malaysian Sunshine Data
    International Journal of Energy Research, 1998
    Co-Authors: Yusof M Sulaiman, Mahdi Abd Wahab, Azmi Zakaria
    Abstract:

    A 10-year Malaysian Sunshine Data of four stations were fitted to three models, namely the Bendt, Hollands and Huget and Saunier models. Distribution parameters of the models were determined from the values of the observed mean of the Sunshine Data. The Kolmogorov–Smirnov test was applied to determine the goodness of fit. It was found that the Saunier model was suitable for the Petaling Jaya and Subang stations while the Hollands and Huget model well suited the Bayan Lepas and Kota Bharu stations. The Bendt model did not give a good fit for all stations. It was also found that for the months that have the same observed mean but different observed standard deviations the distribution models were able to fit well only if the estimated standard deviations were close in value to the observed standard deviations.

K Zabara - One of the best experts on this subject based on the ideXlab platform.

  • study of the weather from Sunshine Data
    Renewable Energy, 1993
    Co-Authors: K Zabara, P Yianoulis
    Abstract:

    Of considerable interest to solar energy applications is the sequence of days of “good” or “bad” weather. In this work we study the dependence of the weather on that of the 2 days before, based on Sunshine Data for a period of 30 years. The results show that this varies considerably during the year and is a function of the daily relative Sunshine (DRS). We also present the generation of sequence of k consecutive days during which the DRS is greater or less (“good” or “bad” weather) than a value x(0 < x < 1).

  • conditional probabilities of daily relative Sunshine Data and the dependence on the weather of the previous day
    Solar Energy, 1992
    Co-Authors: K Zabara, P Yianoulis
    Abstract:

    Abstract In this paper, the conditional probabilities p11(m, x) and p01(m, x) of the daily relative Sunshine (DRS) are estimated for each month m, using available Data for 30 years. p11(m, x) (p01(m, x)) is the probability that the DRS of a day for a certain month is greater than x, (o

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