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  • Open Access


    Determination of Effectiveness of Energy Management System in Buildings

    Vivash Karki1, Roseline Mostafa2, Bhaskaran Gopalakrishnan2,*, Derek R. Johnson3

    Energy Engineering, Vol.120, No.2, pp. 561-586, 2023, DOI:10.32604/ee.2023.025218

    Abstract Building Energy Management Systems (BEMS) are computer-based systems that aid in managing, controlling, and monitoring the building technical services and energy consumption by equipment used in the building. The effectiveness of BEMS is dependent upon numerous factors, among which the operational characteristics of the building and the BEMS control parameters also play an essential role. This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS. The simulation tool gives the user the flexibility to understand the potential energy savings by employing specific BEMS control and help… More > Graphic Abstract

    Determination of Effectiveness of Energy Management System in Buildings

  • Open Access


    Cherenkov Radiation: A Stochastic Differential Model Driven by Brownian Motions

    Qingqing Li1,2, Zhiwen Duan1,2,*, Dandan Yang1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 155-168, 2023, DOI:10.32604/cmes.2022.019249

    Abstract With the development of molecular imaging, Cherenkov optical imaging technology has been widely concerned. Most studies regard the partial boundary flux as a stochastic variable and reconstruct images based on the steadystate diffusion equation. In this paper, time-variable will be considered and the Cherenkov radiation emission process will be regarded as a stochastic process. Based on the original steady-state diffusion equation, we first propose a stochastic partial differential equation model. The numerical solution to the stochastic partial differential model is carried out by using the finite element method. When the time resolution is high enough, the numerical solution of the… More >

  • Open Access


    Seismic Liquefaction Resistance Based on Strain Energy Concept Considering Fine Content Value Effect and Performance Parametric Sensitivity Analysis

    Nima Pirhadi1, Xusheng Wan1, Jianguo Lu1, Jilei Hu2,3,*, Mahmood Ahmad4,5, Farzaneh Tahmoorian6

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 733-754, 2023, DOI:10.32604/cmes.2022.022207

    Abstract Liquefaction is one of the most destructive phenomena caused by earthquakes, which has been studied in the issues of potential, triggering and hazard analysis. The strain energy approach is a common method to investigate liquefaction potential. In this study, two Artificial Neural Network (ANN) models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept (W) by using laboratory test data. A large database was collected from the literature. One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model. To investigate the complex influence… More >

  • Open Access


    New Hybrid EWMA Charts for Efficient Process Dispersion Monitoring with Application in Automobile Industry

    Xuechen Liu1, Majid Khan2, Zahid Rasheed3, Syed Masroor Anwar4,*, Muhammad Arslan5

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1171-1195, 2022, DOI:10.32604/cmes.2022.019199

    Abstract The EWMA charts are the well-known memory-type charts used for monitoring the small-to-intermediate shifts in the process parameters (location and/or dispersion). The hybrid EWMA (HEWMA) charts are enhanced version of the EWMA charts, which effectively monitor the process parameters. This paper aims to develop two new uppersided HEWMA charts for monitoring shifts in process variance, i.e., HEWMA1 and HEWMA2 charts. The design structures of the proposed HEWMA1 and HEWMA2 charts are based on the concept of integrating the features of two EWMA charts. The HEWMA1 and HEWMA2 charts plotting statistics are developed using one EWMA statistic as input for the… More >

  • Open Access


    Bayesian Approximation Techniques for the Generalized Inverted Exponential Distribution

    Rana A. Bakoban, Maha A. Aldahlan*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 129-142, 2022, DOI:10.32604/iasc.2022.018041

    Abstract In this article, Bayesian techniques are adopted to estimate the shape parameter of the generalized inverted exponential distribution (GIED) in the case of complete samples. Normal approximation, Lindley’s approximation, and Tierney and Kadane’s approximation are used for deriving Bayesian estimators. Different informative priors are considered, such as Jeffrey’s prior, Quasi prior, modified Jeffrey’s prior, and the extension of Jeffrey’s prior. Non-informative priors are also used, including Gamma prior, Pareto prior, and inverse Levy prior. The Bayesian estimators are derived under the quadratic loss function. Monte Carlo simulations are carried out to make a comparison among estimators based on the mean… More >

  • Open Access


    The Arcsine-X Family of Distributions with Applications to Financial Sciences

    Yen Liang Tung1, Zubair Ahmad2, Eisa Mahmoudi2,*

    Computer Systems Science and Engineering, Vol.39, No.3, pp. 351-363, 2021, DOI:10.32604/csse.2021.014270

    Abstract The heavy-tailed distributions are very useful and play a major role in actuary and financial management problems. Actuaries are often searching for such distributions to provide the best fit to financial and economic data sets. In the current study, a prominent method to generate new distributions useful for modeling heavy-tailed data is considered. The proposed family is introduced using trigonometric function and can be named as the Arcsine-X family of distributions. For the purposes of the demonstration, a specific sub-model of the proposed family, called the Arcsine-Weibull distribution is considered. The maximum likelihood estimation method is adopted for estimating the… More >

  • Open Access


    Monte Carlo Simulation of Fractures Using Isogeometric Boundary Element Methods Based on POD-RBF

    Haojie Lian1, Zhongwang Wang2,3,*, Haowen Hu3, Shengze Li4, Xuan Peng5, Leilei Chen2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 1-20, 2021, DOI:10.32604/cmes.2021.016775

    Abstract This paper presents a novel framework for stochastic analysis of linear elastic fracture problems. Monte Carlo simulation (MCs) is adopted to address the multi-dimensional uncertainties, whose computation cost is reduced by combination of Proper Orthogonal Decomposition (POD) and the Radial Basis Function (RBF). In order to avoid re-meshing and retain the geometric exactness, isogeometric boundary element method (IGABEM) is employed for simulation, in which the Non-Uniform Rational B-splines (NURBS) are employed for representing the crack surfaces and discretizing dual boundary integral equations. The stress intensity factors (SIFs) are extracted by M integral method. The numerical examples simulate several cracked structures… More >

  • Open Access


    Identification of Abnormal Patterns in AR (1) Process Using CS-SVM

    Hongshuo Zhang1, Bo Zhu1,*, Kaimin Pang1, Chunmei Chen1, Yuwei Wan2

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 797-810, 2021, DOI:10.32604/iasc.2021.017232

    Abstract Using machine learning method to recognize abnormal patterns covers the shortage of traditional control charts for autocorrelation processes, which violate the applicable conditions of the control chart, i.e., the independent identically distributed (IID) assumption. In this study, we propose a recognition model based on support vector machine (SVM) for the AR (1) type of autocorrelation process. For achieving a higher recognition performance, the cuckoo search algorithm (CS) is used to optimize the two hyper-parameters of SVM, namely the penalty parameter c and the radial basis kernel parameter g. By using Monte Carlo simulation methods, the data sets containing samples of… More >

  • Open Access


    Modeling COVID-19 Pandemic Dynamics in Two Asian Countries

    Jin Zhao1, Zubair Ahmad2,*, Zahra Almaspoor2, M. El-Morshedy3,4, Ahmed Z. Afify5

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 965-977, 2021, DOI:10.32604/cmc.2021.014553

    Abstract The current epidemic outbreak COVID-19 first took place in the Wuhan city of China and then spread worldwide. This deadly disease affected millions of people and compelled the governments and other concerned institutions to take serious actions. Around 0.28 million people have died from the COVID-19 outbreak as of May 11, 2020, 05:41 GMT, and the number is still increasing exponentially. The results of any scientific investigation of this phenomenon are still to come. However, now it is urgently needed to evaluate and compare the disease dynamics to improve the quarantine activities and the level of individual protection, to at… More >

  • Open Access


    Sensitivity of Sample for Simulation-Based Reliability Analysis Methods

    Xiukai Yuan1,2,*, Jian Gu1, Shaolong Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 331-357, 2021, DOI:10.32604/cmes.2021.010482

    Abstract In structural reliability analysis, simulation methods are widely used. The statistical characteristics of failure probability estimate of these methods have been well investigated. In this study, the sensitivities of the failure probability estimate and its statistical characteristics with regard to sample, called ‘contribution indexes’, are proposed to measure the contribution of sample. The contribution indexes in four widely simulation methods, i.e., Monte Carlo simulation (MCS), importance sampling (IS), line sampling (LS) and subset simulation (SS) are derived and analyzed. The proposed contribution indexes of sample can provide valuable information understanding the methods deeply, and enlighten potential improvement of methods. It… More >

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