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  • Open Access


    Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

    Murad A. A. Almekhlafi1, Fahd N. Al-Wesabi2,3, Majdy M. Eltahir4, Anwer Mustafa Hilal5, Amin M. El-Kustaban6, Abdelwahed Motwakel5, Ishfaq Yaseen5, Manar Ahmed Hamza5,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3113-3129, 2022, DOI:10.32604/cmc.2022.024355

    Abstract Energy is an essential element for any civilized country's social and economic development, but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the ecosystem. The Republic of Yemen has very good potential to use renewable energy. Unfortunately, we find few studies on renewable wind energy in Yemen. Given the lack of a similar analysis for the coastal city, this research newly investigates wind energy's potential near the Almukalla area by analyzing wind characteristics. Thus, evaluation, model identification, determination of available energy density, computing the capacity factors… More >

  • Open Access


    A New Rayleigh Distribution: Properties and Estimation Based on Progressive Type-II Censored Data with an Application

    Ali Algarni, Abdullah M. Almarashi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 379-396, 2022, DOI:10.32604/cmes.2022.017714

    Abstract In this paper, we propose a new extension of the traditional Rayleigh distribution called the modified Kies Rayleigh distribution. The new distribution contains one scale and one shape parameter and its hazard rate function can be increasing and bathtub-shaped. Some mathematical properties of the new distribution are derived including quantiles and moments. The parameters of modified Kies Rayleigh distribution are estimated based on progressively Type-II censored data. For this purpose, we consider two estimation methods, namely maximum likelihood and maximum product of spacing estimation methods. To compare the efficiency of the proposed estimators, a simulation More >

  • Open Access


    Statistical Inference of Sine Inverse Rayleigh Distribution

    Abdullah, Ali H. Ahmadini*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 405-414, 2022, DOI:10.32604/csse.2022.020079

    Abstract We study in this manuscript a new one-parameter model called sine inverse Rayleigh (SIR) model that is a new extension of the classical inverse Rayleigh model. The sine inverse Rayleigh model is aiming to provide more fitting for real data sets of purposes. The proposed extension is more flexible than the original inverse Rayleigh (IR) model and it hasmany applications in physics and medicine. The sine inverse Rayleigh distribution can havea uni-model and right skewed probability density function (PDF). The hazard rate function (HRF) of sine inverse Rayleigh distribution can be increasing and J-shaped. Several More >

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