Yan Shi¹, Wenjie Li¹, Gongbo Fan^2,*, Luxi Zhang¹, Fengjiu Yang¹

Energy Engineering, Vol.121, No.2, pp. 461-482, 2024, DOI:10.32604/ee.2023.043835

Abstract Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation, this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side. A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation, with the overarching goal of optimizing the system for low-carbon operation. To begin with, an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side… More >

Sunisa Junnumtuam, Sa-Aat Niwitpong^*, Suparat Niwitpong

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1229-1254, 2023, DOI:10.32604/cmes.2022.022098

Abstract A new three-parameter discrete distribution called the zero-inflated cosine geometric (ZICG) distribution is proposed for the first time herein. It can be used to analyze over-dispersed count data with excess zeros. The basic statistical properties of the new distribution, such as the moment generating function, mean, and variance are presented. Furthermore, confidence intervals are constructed by using the Wald, Bayesian, and highest posterior density (HPD) methods to estimate the true confidence intervals for the parameters of the ZICG distribution. Their efficacies were investigated by using both simulation and real-world data comprising the number of daily COVID-19 positive cases at the… More > Graphic Abstract

Rashad Bantan¹, Amal S. Hassan², Ehab Almetwally³, M. Elgarhy⁴, Farrukh Jamal⁵, Christophe Chesneau⁶, Mahmoud Elsehetry^7,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2859-2875, 2021, DOI:10.32604/cmc.2021.015422

Abstract Accelerated life testing has been widely used in product life testing experiments because it can quickly provide information on the lifetime distributions by testing products or materials at higher than basic conditional levels of stress, such as pressure, temperature, vibration, voltage, or load to induce early failures. In this paper, a step stress partially accelerated life test (SS-PALT) is regarded under the progressive type-II censored data with random removals. The removals from the test are considered to have the binomial distribution. The life times of the testing items are assumed to follow length-biased weighted Lomax distribution. The maximum likelihood method… More >

Sanaa Al-Marzouki¹, Farrukh Jamal², Christophe Chesneau^3,*, Mohammed Elgarhy⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521

Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the… More >

He Ni^1,*, Yongqiao Wang¹, Buyun Xu²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 227-236, 2020, DOI:10.31209/2019.100000068

Abstract The paper presents a probabilistic clustering approach based on self-organizing learning algorithm and recursive Bayesian estimation. The model is built upon the principle that the market data space is multimodal and can be described by a mixture of Gaussian distributions. The model parameters are approximated by a stochastic recursive Bayesian learning: searches for the maximum a posterior solution at each step, stochastically updates model parameters using a “dualneighbourhood” function with adaptive simulated annealing, and applies profile likelihood confidence interval to avoid prolonged learning. The proposed model is based on a number of pioneer works, such as Mixture Gaussian Autoregressive Model,… More >

Roberto Bellas^{1, *}, Javier Martínez¹, Ignacio Rivera², Ramón Touza², Miguel Gómez¹, Rafael Carreño¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 971-995, 2020, DOI:10.32604/cmes.2020.07530

Abstract The study of emergency evacuation in public spaces, buildings and large ships may present parallel characteristic in terms of complexity of the layout but there are also significant differences that can hindering passengers to reach muster stations or the lifeboats. There are many hazards on a ship that can cause an emergency evacuation, the most severe result in loss of lives. Providing safe and effective evacuation of passengers from ships in an emergency situation becomes critical. Recently, computer simulation has become an indispensable technology in various fields, among them, the evacuation models that recently evolved incorporating human behavioral factors. In… More >

W. Zhang¹, X. Han^1,2, J. Liu¹, Z. H. Tan¹

CMC-Computers, Materials & Continua, Vol.26, No.3, pp. 201-226, 2011, DOI:10.3970/cmc.2011.026.201

Abstract The uncertainty inverse problems with insufficiency and imprecision in the input and/or output parameters are widely existing and unsolved in the practical engineering. The insufficiency refers to the partly known parameters in the input and/or output, and the imprecision refers to the measurement errors of these ones. In this paper, a combined method is proposed to deal with such problems. In this method, the imprecision of these known parameters can be described by probability distribution with a certain mean value and variance. Sensitive matrix method is first used to transform the insufficient formulation in the input and/or output to a… More >

Meng Li¹, Kanhua Su¹, Zijian Li², Dongjie Li³, Lifu Wan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.4, pp. 475-495, 2017, DOI:10.3970/cmes.2017.113.475

Abstract With the consideration of the randomness of complex geologic parameters for ultra-deep wells, an uncertainty analysis method is presented for the extrusion load on casing in ultra-deep wells through complex formation at a certain confidence level. Based on the extrusion load model for casing in ultra-deep wells and the prerequisite of integrity of formation-cement ring-casing, the probability and statistics theory is introduced and the sensitivity analysis on the uncertainty of extrusion load on casing is conducted. The distribution types of each formation parameters are determined statistically. The distribution type and distribution function of the extrusion load on casing are derived.… More >