A New Extended-Gamma Family of Distributions: Properties and Applications

Lahcene, Bachioua

doi:10.26855/jamc.2021.03.002

Cited by 11 publications

(10 citation statements)

References 10 publications

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“…The above-mentioned log-normal distribution uses the following mean and standard deviation (SD) formulas [40] for the droplet diameter (d):…”

Section: Droplet Size Distributionmentioning

confidence: 99%

Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations

Vhora,

Janiga,

Lorenz

et al. 2024

Applied Sciences

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The interfacial area between two phases plays a crucial role in the mass transfer rate of gas–liquid processes such as absorption. In this context, the droplet size distribution within the flow field of a droplet-based absorber significantly affects the surface area, thereby influencing the absorption efficiency. This study focuses on developing a computational fluid dynamics (CFD) model to predict the size and distribution of water droplets free-falling in a transparent square tube. This model serves as a digital twin of our experimental setup, enabling a comparative analysis of experimental and computational results. For the accurate measurement of droplet size and distribution, specialized experimental equipment was developed, and a high-speed camera along with Fiji software was used for the capturing and processing of droplet images. At the point of injection and at two different heights, the sizes and distributions of falling droplets were measured using this setup. The interaction between the liquid water droplets and the gas phase within the square tube was modeled using the Eulerian–Lagrangian (E-L) framework in the STAR-CCM+ software. The E-L multiphase CFD model yielded approximations with errors ranging from 11 to 27% for various average mean diameters, including d10, d20, d30, and d32, of the liquid droplets at two distinct heights (200 mm and 400 mm) for both nozzle plates. This comprehensive approach provides valuable insights into the dynamics of droplet-based absorption processes.

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“…The above-mentioned log-normal distribution uses the following mean and standard deviation (SD) formulas [40] for the droplet diameter (d):…”

Section: Droplet Size Distributionmentioning

confidence: 99%

Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations

Vhora,

Janiga,

Lorenz

et al. 2024

Applied Sciences

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“…The models will be fitted by using available softwares and languages like EViews 8, R and/or SAS etc. Due to the scarcity of available data, its limitations and the accelerated impact of the fluctuations experienced by the Kingdom, which caused severe changes that appear during the daily follow-up of the announced results, especially in the first six months of the previous year, the researcher was forced during the statistical treatment to use the cumulative data to predict the number of cases declared per month in The Kingdom of Saudi Arabia, and with this, after treatment, the results of the cumulative number of COVID-19 cases of confirmed cases, deaths, and recoveries appeared in an increasing exponential manner, which can be described as a generalized exponential model over time [3].…”

Section: Multivariate Modelsmentioning

confidence: 99%

“…Statistics, mathematics, and knowledge related to nature and how it is applied constitute hyper-thinking and data analysis, simulating the human mind and its ways of working, such as its ability to think, discover and benefit from past experiences, machine learning to collect, monitor and analyze data, and the system's ability to correctly interpret data, learn from it, and use knowledge. [3]. The field of data science is one of the most in-demand fields in the labor market in the world during the past five years, and according to the report of Glassdoor, it is the most sought-after job in 2018 in the US market, which is also the view of the annual LinkedIn report for 2017.…”

Section: Introductionmentioning

confidence: 99%

On Statistical Analysis of Forecasting COVID-19 for the Upcoming Months in the Kingdom of Saudi Arabia

Lahcene

2021

ijsmr

Self Cite

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This paper presents a statistical analysis using fitted prediction models that revealed a high exponential growth in the number of confirmed cases, deaths, and treated case processes based on our model predictions and the results of experimental COVID-19 predictions. The studies aimed to build inductive statistical models using the automatic integrated mean regression model methodology, and its preferred method for tracking data that represent the spread of the epidemic and then effectively predicting its numbers over the next six months, in addition to the number of deaths and cases that responded to recovery treatment using ARIMA. Moreover, the number of infected cases per day is expected to stabilize less than 500, daily deaths are less than 15, and this situation will continue until the largest number of people are vaccinated in order to obtain herd immunity, and control the causes of the spread of the epidemic such as human gatherings and friction. Among individuals, in addition to obtaining the appropriate vaccine in the future, especially since the Kingdom of Saudi Arabia is waiting for this year's pilgrims from inside and outside the Kingdom, the results of this work will be useful for practitioners in various fields of theoretical and applied sciences.

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“…They are ideally suited for the prediction and forecasting of real-world issue modeling. There are several ways for generalizing distributions, including: beta-G [1]; generalized Kumaraswamy-G [2]; Weibull odd Burr III-G [3]; Gompertz-G [4]; a new power Topp-Leone-G [5]; exponentiated Kumaraswamy-G [6]; type I half logistic Weibull-G [7]; type I half logistic Burr X-G [8]; the transmuted Burr X-G in [9]; odd power Lindley-G [10]; gamma Kumaraswamy-G [11]; new extended cosine-G in [12]; extended-gamma-G [13]; odd Chen-G [14]; Kumaraswamy type I half logistic-G [15]; log-logistic-G [16]; gamma-G [17]; Kumaraswamy Poisson-G [18]; Kumaraswamy Kumaraswamy-G [19]; additive odd-G [20]; beta generalized Marshall-Olkin Kumaraswamy-G [21]; extended alpha power transformed family of distributions [22]; odd Burr X-G [23]; the Weibull−G in [24]; type II half logistic-G [25]; sec-G [26]; generalized odd linear exponential-G [27]; Stacy-G [28]; odd Perks-G [29]; sine Topp-Leone-G [30]; Kumaraswamy generalized Marshall-Olkin-G [31]; arcsine-exponentiated-X family-G [32]; odd exponentiated half logistic-G [33]; Kumaraswamy Marshall-Olkin-G [34]; and sineexponentiated Weibull−H [35], among others. Recently, ref.…”

Section: Introductionmentioning

confidence: 99%

Half Logistic Inverted Nadarajah–Haghighi Distribution under Ranked Set Sampling with Applications

et al. 2023

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In this paper, we present the half logistic inverted Nadarajah–Haghigh (HL-INH) distribution, a novel extension of the inverted Nadarajah–Haghigh (INH) distribution. The probability density function (PDF) for the HL-INH distribution might have a unimodal, right skewness, or heavy-tailed shape for numerous parameter values; however, the shape forms of the hazard rate function (HRF) for the HL-INH distribution may be decreasing. Four specific entropy measurements were investigated. Some useful expansions for the HL-INH distribution were investigated. Several statistical and computational features of the HL-INH distribution were calculated. Using simple (SRS) and ranked set sampling (RSS), the parameters for the HL-INH distribution were estimated using the maximum likelihood (ML) technique. A simulation analysis was executed in order to determine the model parameters of the HL-INH distribution using the SRS and RSS methods, and RSS was shown to be more efficient than SRS. We demonstrate that the HL-INH distribution is more adaptable than the INH distribution and other statistical distributions when utilizing three real-world datasets.

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A New Extended-Gamma Family of Distributions: Properties and Applications

Abstract: How to cite this paper: Bachioua Lahcene.

Cited by 11 publications

References 10 publications

Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations

Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations

On Statistical Analysis of Forecasting COVID-19 for the Upcoming Months in the Kingdom of Saudi Arabia

Half Logistic Inverted Nadarajah–Haghighi Distribution under Ranked Set Sampling with Applications

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