Okechukwu J. Obulezi^1,*, Hatem E. Semary², Sadia Nadir³, Chinyere P. Igbokwe⁴, Gabriel O. Orji¹, A. S. Al-Moisheer², Mohammed Elgarhy⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2991-3027, 2025, DOI:10.32604/cmes.2025.069553 - 30 September 2025

Abstract This study introduces the type-I heavy-tailed Burr XII (TIHTBXII) distribution, a highly flexible and robust statistical model designed to address the limitations of conventional distributions in analyzing data characterized by skewness, heavy tails, and diverse hazard behaviors. We meticulously develop the TIHTBXII’s mathematical foundations, including its probability density function (PDF), cumulative distribution function (CDF), and essential statistical properties, crucial for theoretical understanding and practical application. A comprehensive Monte Carlo simulation evaluates four parameter estimation methods: maximum likelihood (MLE), maximum product spacing (MPS), least squares (LS), and weighted least squares (WLS). The simulation results consistently show… More >

Yi Zhang¹, Wenliang Zhu^1,*, Hanbin Wang¹, Chun Tian², Jiajun Zhou²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2873-2891, 2025, DOI:10.32604/cmes.2025.068951 - 30 September 2025

Abstract Aiming to address the challenge of directly measuring the real-time adhesion coefficient between wheels and rails, this paper proposes an online estimation algorithm for the adhesion coefficient based on parameter estimation. Firstly, a force analysis of the single-wheel pair model of the train is conducted to derive the calculation relationship for the wheel-rail adhesion coefficient in train dynamics. Then, an estimator based on parameter estimation is designed, and its stability is verified. This estimator is combined with the wheelset force analysis to estimate the wheel-rail adhesion coefficient. Finally, the approach is validated through joint simulations… More >

Khizer Mehmood¹, Naveed Ishtiaq Chaudhary^2,*, Zeshan Aslam Khan³, Khalid Mehmood Cheema⁴, Muhammad Asif Zahoor Raja², Sultan S. Alshamrani⁵, Kaled M. Alshmrany⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1809-1841, 2025, DOI:10.32604/cmes.2025.064900 - 30 May 2025

Abstract Aquila Optimizer (AO) is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey. AO is applied in various applications and its numerous variants were proposed in the literature. However, chaos theory has not been extensively investigated in AO. Moreover, it is still not applied in the parameter estimation of electro-hydraulic systems. In this work, ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique. An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation (CEC) functions… More >

Amlak Abaza¹, Ragab A. El-Sehiemy^1,6, Mona Gafar^2,3,*, Ahmed Bayoumi^4,5

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 723-745, 2025, DOI:10.32604/cmes.2025.059625 - 11 April 2025

Abstract Promoting the high penetration of renewable energies like photovoltaic (PV) systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution grids. This study measures the effectiveness of the Puma optimizer (PO) algorithm in parameter estimation of PSC (perovskite solar cells) dynamic models with hysteresis consideration considering the electric field effects on operation. The models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs accurately. The PO optimizes the proposed modified triple diode model (TDM) with a variable voltage capacitor… More >

Muhammad Altaf Khan^1,*, Mahmoud H. DarAssi², Irfan Ahmad³, Noha Mohammad Seyam⁴, Ebraheem Alzahrani⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1365-1394, 2024, DOI:10.32604/cmes.2024.053681 - 27 September 2024

Abstract A mathematical model is designed to investigate Tuberculosis (TB) disease under the vaccination, treatment, and environmental impact with real cases. First, we introduce the model formulation in non-integer order derivative and then, extend the model into fractional order derivative. The fractional system’s existence, uniqueness, and other relevant properties are shown. Then, we study the stability analysis of the equilibrium points. The disease-free equilibrium (DFE) is locally asymptotically stable (LAS) when . Further, we show the global asymptotical stability (GAS) of the endemic equilibrium (EE) for and for . The existence of bifurcation analysis in the More >

Bin Liu¹, Shuai Liang¹, Renjie Ding¹, Shuguang Li^2,*

Energy Engineering, Vol.121, No.3, pp. 729-746, 2024, DOI:10.32604/ee.2023.044224 - 27 February 2024

Abstract The application of traditional synchronous measurement methods is limited by frequent fluctuations of electrical signals and complex frequency components in distribution networks. Therefore, it is critical to find solutions to the issues of multifrequency parameter estimation and synchronous measurement estimation accuracy in the complex environment of distribution networks. By utilizing the multifrequency sensing capabilities of discrete Fourier transform signals and Taylor series for dynamic signal processing, a multifrequency signal estimation approach based on HT-IpDFT-STWLS (HIpST) for distribution networks is provided. First, by introducing the Hilbert transform (HT), the influence of noise on the estimation algorithm… More >

Jiepeng Yao^1,2, Zhanjia Peng^1,2, Jingjing Liu^1,2, Chengxiao Fan^1,2, Zhongyi Wang^1,2,3, Lan Huang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2243-2265, 2023, DOI:10.32604/cmes.2023.028101 - 03 August 2023

Abstract In the establishment of differential equations, the determination of time-varying parameters is a difficult problem, especially for equations related to life activities. Thus, we propose a new framework named BioE-PINN based on a physical information neural network that successfully obtains the time-varying parameters of differential equations. In the proposed framework, the learnable factors and scale parameters are used to implement adaptive activation functions, and hard constraints and loss function weights are skillfully added to the neural network output to speed up the training convergence and improve the accuracy of physical information neural networks. In this… 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 >

Wentao Liu, Junxia Ma, Weili Xiong^*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 873-892, 2023, DOI:10.32604/cmes.2022.020565 - 31 August 2022

Abstract This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances. A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data. Based on the bilinear state observer, a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function. The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance. Furthermore, to More >

Mustafa Kamal^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1239-1269, 2022, DOI:10.32604/cmes.2022.017532 - 30 December 2021

Abstract In general, simple subsystems like series or parallel are integrated to produce a complex hybrid system. The reliability of a system is determined by the reliability of its constituent components. It is often extremely difficult or impossible to get specific information about the component that caused the system to fail. Unknown failure causes are instances in which the actual cause of system failure is unknown. On the other side, thanks to current advanced technology based on computers, automation, and simulation, products have become incredibly dependable and trustworthy, and as a result, obtaining failure data for… More >