Naif Alotaibi¹, A. S. Al-Moisheer², Ibrahim Elbatal¹, Mohammed Elgarhy^3,4, Ehab M. Almetwally^1,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2795-2823, 2024, DOI:10.32604/cmes.2024.049188 - 08 July 2024

Abstract This article introduces a novel variant of the generalized linear exponential (GLE) distribution, known as the sine generalized linear exponential (SGLE) distribution. The SGLE distribution utilizes the sine transformation to enhance its capabilities. The updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability issues. The suggested model incorporates a hazard rate function (HRF) that may display a rising, J-shaped, or bathtub form, depending on its unique characteristics. This model includes many well-known lifespan distributions as separate sub-models. The suggested model is accompanied with a range of More >

Jamal N. Al Abbasi¹, Ahmed Z. Afify^2,*, Badr Alnssyan^3,*, Mustafa S. Shama^4,5

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 513-536, 2024, DOI:10.32604/cmes.2024.046533 - 16 April 2024

Abstract This study proposes a new flexible family of distributions called the Lambert-G family. The Lambert family is very flexible and exhibits desirable properties. Its three-parameter special sub-models provide all significant monotonic and non-monotonic failure rates. A special sub-model of the Lambert family called the Lambert-Lomax (LL) distribution is investigated. General expressions for the LL statistical properties are established. Characterizations of the LL distribution are addressed mathematically based on its hazard function. The estimation of the LL parameters is discussed using six estimation methods. The performance of this estimation method is explored through simulation experiments. The More >

Heba S. Mohammed¹, Mazen Nassar^2,3, Refah Alotaibi¹, Ahmed Elshahhat^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2761-2793, 2023, DOI:10.32604/cmes.2023.028826 - 03 August 2023

Abstract A new extended exponential lifetime model called Harris extended-exponential (HEE) distribution for data modelling with increasing and decreasing hazard rate shapes has been considered. In the reliability context, researchers prefer to use censoring plans to collect data in order to achieve a compromise between total test time and/or test sample size. So, this study considers both maximum likelihood and Bayesian estimates of the Harris extended-exponential distribution parameters and some of its reliability indices using a progressive Type-II censoring strategy. Under the premise of independent gamma priors, the Bayesian estimation is created using the squared-error and… More >

Hassan Okasha^1,2, Mazen Nassar^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2219-2241, 2023, DOI:10.32604/cmes.2023.028783 - 03 August 2023

Abstract In this paper, we introduce a new four-parameter version of the traditional Weibull distribution. It is able to provide seven shapes of hazard rate, including constant, decreasing, increasing, unimodal, bathtub, unimodal then bathtub, and bathtub then unimodal shapes. Some basic characteristics of the proposed model are studied, including moments, entropies, mean deviations and order statistics, and its parameters are estimated using the maximum likelihood approach. Based on the asymptotic properties of the estimators, the approximate confidence intervals are also taken into consideration in addition to the point estimators. We examine the effectiveness of the maximum More >

Aisha Fayomi¹, Christophe Chesneau^2,*, Farrukh Jamal³, Ali Algarni¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2371-2403, 2023, DOI:10.32604/cmes.2023.027000 - 09 March 2023

Abstract In this article, we highlight a new three-parameter heavy-tailed lifetime distribution that aims to extend the modeling possibilities of the Lomax distribution. It is called the extended Lomax distribution. The considered distribution naturally appears as the distribution of a transformation of a random variable following the logweighted power distribution recently introduced for percentage or proportion data analysis purposes. As a result, its cumulative distribution has the same functional basis as that of the Lomax distribution, but with a novel special logarithmic term depending on several parameters. The modulation of this logarithmic term reveals new types… More >

Refah Alotaibi¹, Hassan Okasha^2,3, Mazen Nassar^2,4, Ahmed Elshahhat^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2065-2089, 2023, DOI:10.32604/cmes.2023.023408 - 23 November 2022

Abstract This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique. We refer to the new model as modified alpha power transformed Weibull distribution. The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions, which are quite familiar in environmental investigations. Its hazard rate function can be decreasing, increasing, bathtub and upside-down then bathtub shaped. Diverse structural properties of the proposed model are acquired including quantile function, moments, entropies, order statistics, More >

Mohamed Kayid^*, Tareq Alsayed

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1847-1860, 2022, DOI:10.32604/cmc.2022.025401 - 24 February 2022

Abstract An important property that any lifetime model should satisfy is scale invariance. In this paper, a new scale-invariant quasi-inverse Lindley (QIL) model is presented and studied. Its basic properties, including moments, quantiles, skewness, kurtosis, and Lorenz curve, have been investigated. In addition, the well-known dynamic reliability measures, such as failure rate (FR), reversed failure rate (RFR), mean residual life (MRL), mean inactivity time (MIT), quantile residual life (QRL), and quantile inactivity time (QIT) are discussed. The FR function considers the decreasing or upside-down bathtub-shaped, and the MRL and median residual lifetime may have a bathtub-shaped… More >

Walid Aydi^1,3,*, Fuad S. Alduais^2,4

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4033-4050, 2022, DOI:10.32604/cmc.2022.023119 - 07 December 2021

Abstract The Weibull distribution is regarded as among the finest in the family of failure distributions. One of the most commonly used parameters of the Weibull distribution (WD) is the ordinary least squares (OLS) technique, which is useful in reliability and lifetime modeling. In this study, we propose an approach based on the ordinary least squares and the multilayer perceptron (MLP) neural network called the OLSMLP that is based on the resilience of the OLS method. The MLP solves the problem of heteroscedasticity that distorts the estimation of the parameters of the WD due to the… More >

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 - 29 November 2021

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 >

Azam Zaka¹, Riffat Jabeen^2,*, Kanwal Iqbal Khan³

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4781-4802, 2022, DOI:10.32604/cmc.2022.020316 - 11 October 2021

Abstract The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution. It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement. The current study introduces control charts that help the manufacturing concerns to keep the production process in control. It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance. The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts. The More >