Rules-Based Energy Management System for an EV Charging Station Nanogrid: A Stochastic Analysis by Gabriel Henrique Danielsson, Leonardo Nogueira Fontoura da Silva, Joelson Lopes da Paixão, Alzenira da Rosa Abaide, Nelson Knak Neto

“…The methodology includes forecasting models based on an Artificial Neural Network for photovoltaic generation, a parametric estimation for wind generation, and a Monte Carlo simulation to predict the energy consumption of electric vehicles. …”
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Characterization, Distribution, and Risk Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) in the Workplaces of an Electric Arc Furnace (EAF) Steelmaking Factory by Ying-Fang Wang, Riza P. Gumaling, Mei-Ru Chen, Yu-Chieh Kuo, Lin-Chi Wang

“…Abstract This study measured workplace polycyclic aromatic hydrocarbons (PAHs) in an electric arc furnace (EAF) factory during regular and maintenance periods and estimated workers’ lung cancer risk from 40 years of exposure using Monte Carlo Simulation. Workers were grouped into three similar exposure groups (SEGs) based on their tasks in melting, ladling and casting areas of the EAF factory. …”
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Investigation of the Atomic Structure of Ge-Sb-Se Chalcogenide Glasses by M. Fabian, N. Dulgheru, K. Antonova, A. Szekeres, M. Gartner

“…These results are in agreement with the Reverse Monte Carlo models, which define the Ge and Sb environment.…”
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Uncertainty quantification of CT regularized reconstruction within the Bayesian framework by Negin Khoeiniha, Patricio Guerrero, Wim Dewulf

“…This method significantly reduces computational and storage demands compared to classic Monte Carlo simulations while incorporating regularization techniques. …”
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Predicting the adsorption of -perfluorohexane in BAM-P109 standard activated carbon by molecular simulation using SAFT- Mie coarse-grained force fields by Carmelo Herdes, Esther Forte, George Jackson, Erich A Müller

“…The coarse-grained intermolecular potential models are then used to obtain the adsorption isotherm kernels for argon, carbon dioxide, and n -perfluorohexane in graphite slit pores of various widths using Grand Canonical Monte Carlo simulations. A unique and fluid-independent pore size distribution curve with total micropore volume of 0.5802 cm 3 /g is proposed for the BAM-P109. …”
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Extropy estimation of Weibull distribution under upper records by Nour El Houda Zouaoui

“…We apply the Markov Chain Monte Carlo (MCMC) method to provide a Bayesian estimator. …”
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Research and Application of the Solving Method for Robotic Workspace by He Jiawei, Ping Xueliang, Li Zhaoyang, Jiang Yi

“…For the solution of the robotic workspace,on the basis of existing research methods,a new solution method which combines the advantage of Monte- Carlo method with Matlab simulation modeling capability is proposed. …”
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Performance analysis of weighted non-coherent receiver for UWB-PPM signal in multipath channels by WU Jian-jun, LIANG Qing-lin, XIANG Hai-ge

“…The BER performance expressions and weighting coefficients of the weighted non-coherent receiver for the UWB-PPM signal were analytically derived.Subsequently,the analytical results were validated via Monte-Carlo simula-tion,and the impacts of the sub-interval width and the timing error were also numerical analyzed.It is illustrated that the weighted receiver is at least 3dB superior to the conventional non-coherent receiver,and is robust to the variations of sub-integration width and the timing error.…”
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Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model by Mohammad Jasim Mohammad, Sajad Sammer Abd Al-Razzaq

“…This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. …”
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Properties of the coefficient estimators for the linear regression model with heteroskedastic error term by Alfredas Račkauskas, Danas Zuokas

“…For the heteroskedasticity of the changed segment type, using Monte-Carlo method, we investigate empirical properties of the proposed and ordinary least squares (OLS) estimators. …”
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The Exponentiated Exponential-Inverse Weibull Model: Theory and Application to COVID-19 Data in Saudi Arabia by Majdah Mohammed Badr, Ghaida Sobahi

“…The maximum likelihood (ML) estimator (MLE) approach is used to estimate the parameters. A Monte Carlo simulation is done to examine the behavior of the estimators. …”
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Nonstationary INAR(1) Process with th-Order Autocorrelation Innovation by Kaizhi Yu, Hong Zou, Daimin Shi

“…The performance of the autoregressive coefficient estimators is assessed through the Monte Carlo simulations.…”
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Nonparametric Estimation of ATE and QTE: An Application of Fractile Graphical Analysis by Gabriel V. Montes-Rojas

“…In both cases, the estimators are proved to be consistent. Monte Carlo results show a better performance than other procedures based on the propensity score. …”
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Estimation of the Parameters of Burr Type III Distribution Based on Dual Generalized Order Statistics by Chansoo Kim, Woosuk Kim

“…To compare the maximum likelihood estimator and the Bayes estimator of the parameters, Monte Carlo simulation study is performed.…”
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Lattice Methods for Pricing American Strangles with Two-Dimensional Stochastic Volatility Models by Xuemei Gao, Dongya Deng, Yue Shan

“…This proposed method is compared with the least square Monte-Carlo method via numerical examples.…”
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Characterization and Goodness-of-Fit Test of Pareto and Some Related Distributions Based on Near-Order Statistics by Masoumeh Akbari

“…And the power values of the proposed tests are compared with the power values of well-known tests such as Kolmogorov–Smirnov and Cramer-von Mises tests by Monte Carlo simulations.…”
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Kinematics Analysis of the Leg-wheel Walking System of Engineering Machinery with Variable Structure by Luo Jinliang, Wen Qun, He Jialai

“…The kinematics model of walking system with variable structure of engineering machinery is established.The forward kinematics analysis and inverse kinematics analysis of right front leg is conducted,the explicit formulation of the position,velocity and acceleration at the end of right front leg is obtained.With the inverse kinematics analysis,the revolute angle of each joint in the right front leg is got with given end location of right front leg.Based on the kinematics analysis,the working space of the right front leg is solved through Monte Carlo algorithm by Matlab.…”
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A Bayesian model for binary Markov chains by Souad Assoudou, Belkheir Essebbar

“…The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC) techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.…”
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Ecological and human health implications of mercury contamination in the coastal water by A. Mallongi, A.U. Rauf, R.D.P. Astuti, S. Palutturi, H. Ishak

“…Additionally, the Monte Carlo simulation model revealed that the non-carcinogenic risk caused by mercury exposure in adults and children was greater than 1 (Total Hazard Index>1), indicating the health adverse effects for both receptors. …”
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Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches by Mohsin Akram, Muhammad Adnan, Syed Farooq Ali, Jameel Ahmad, Amr Yousef, Tagrid Abdullah N. Alshalali, Zaffar Ahmed Shaikh

“…Bayesian approximation techniques, including Monte Carlo Dropout, Mean Field Variational Inference, and Deterministic Inference, were applied to represent the posterior predictive distribution, allowing us to evaluate uncertainty in model predictions. …”
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