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

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 is reduced. Second, signal frequency… 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

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 paper, taking the electrophysiological differential… 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

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 likelihood estimators of the model’s… 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

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 improve the performance of… More >

Mustafa Kamal^*

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

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 testing such exceptionally reliable items… More >

Abdullah Shoukat¹, Muhammad Ali Mughal^1,*, Saifullah Younus Gondal¹, Farhana Umer², Tahir Ejaz³, Ashiq Hussain¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 269-285, 2022, DOI:10.32604/cmc.2022.021575

Abstract Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using the input-output quantities i.e., voltages,… More >

Ahmed M. Nassef^1,2,*, Hegazy Rezk^1,3

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 171-180, 2022, DOI:10.32604/cmc.2022.019347

Abstract This paper addresses improvements in fractional order (FO) system performance. Although the classical proportional–integral–derivative (PID)-like fuzzy controller can provide adequate results for both transient and steady-state responses in both linear and nonlinear systems, the FOPID fuzzy controller has been proven to provide better results. This high performance was obtained thanks to the combinative benefits of FO and fuzzy-logic techniques. This paper describes how the optimal gains and FO parameters of the FOPID controller were obtained by the use of a modern optimizer, social spider optimization, in order to improve the response of fractional dynamical systems. This group of systems had… More >

A. M. Abdullah¹, Hegazy Rezk^2,3,*, A. Hadad¹, Mohamed K. Hassan^1,4, A. F. Mohamed^1,5

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 619-631, 2021, DOI:10.32604/iasc.2021.018289

Abstract The problem of parameter estimation of the proton exchange membrane fuel cell (PEMFC) model plays a significant role in the simulation and optimization of a PEMFC system. In the current research, a moth flame optimization algorithm (MFOA) is used to identify the best parameters of PEMFC. Two different PEMFCs, Nedstack PS6, 6 kW, and SR-12 PEM 500 W are used to demonstrate the accuracy of the MFOA. Throughout the optimization process, seven unidentified parameters (℥₁, ℥₂, ℥₃, ℥₄, λ, ℛ, and B) of PEMFC are appointed to be decision variables. The fitness function, which needed to be minimum, is represented… More >

Gamal M. Ibrahim¹, Amal S. Hassan², Ehab M. Almetwally^3,*, Hisham M. Almongy⁴

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 353-371, 2021, DOI:10.32604/iasc.2021.017586

Abstract We introduce a new two-parameter lifetime model, referred to alpha power transformed inverted Topp-Leone, derived by combining the alpha power transformation-G family with the inverted Topp-Leone distribution. Structural properties of the proposed distribution are implemented like; quantile function, residual and reversed residual life, Rényi entropy measure, moments and incomplete moments. The maximum likelihood, weighted least squares, maximum product of spacing, and Bayesian methods of estimation are considered. A simulation study is worked out to evaluate the restricted sample properties of the proposed distribution. Numerical results showed that the Bayesian estimates give more accurate results than the corresponding other estimates in… More >

Muhammad Farman¹, Ali Akgül^2,*, Aqeel Ahmad¹, Dumitru Baleanu^3,4,5, Muhammad Umer Saleem⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 753-769, 2021, DOI:10.32604/cmes.2021.014882

Abstract COVID-19 acts as a serious challenge to the whole world. Epidemiological data of COVID-19 is collected through media and web sources to analyze and investigate a system of nonlinear ordinary differential equation to understand the outbreaks of this epidemic disease. We analyze the diseases free and endemic equilibrium point including stability of the model. The certain threshold value of the basic reproduction number R₀ is found to observe whether population is in disease free state or endemic state. Moreover, the epidemic peak has been obtained and we expect a considerable number of cases. Finally, some numerical results are presented which… More >