Integrating Multi-Model Simulations to Address Partial Observability in Population Dynamics: A Python-Based Ecological Tool by Yide Yu, Huijie Li, Yue Liu, Yan Ma

“…WAPET integrates Monte Carlo simulation with ecological models, including Logistic Growth, Random Walk, and Cellular Automata, to provide a multi-perspective assessment of ecological systems. …”
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Dynamic characteristic analysis and load design of large floating structures based on experimental design by Guofeng Zhao, Shifan Zhu

“…The experimental design method based on the plane Monte Carlo method and Latin hypercube sampling method and the fitting method based on the moving least squares and Kriging methods can effectively evaluate the influence of wave parameters on the dynamic response of structures. …”
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Sequencing of game complexes in women’s volleyball: are there differences according to the set played? by Pedro Henrique Cavalcante Vieira, Lorenzo Laporta, Gustavo Ferreira Pedrosa, Augusto Faria de Paula Santana, Auro Barreiros Freire, Crislaine Couto Rangel, Claudio Andre Barbosa de Lira, Filipe Manuel Clemente, Thiago José Leonardi, Gustavo De Conti Teixeira Costa

“…Eigenvector Centrality and Social Network Analysis conducted the connectivity and specificity of relationships as, and inferential analysis was performed using the chi-square test with a Monte Carlo correction. Results The results showed that the highest eigenvalues were for the continuity effect, except for complex 0. …”
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Evaluation of porphyrin molecules as effective corrosion inhibitors for copper alloy in sulfuric acid using both experimental and computational approaches by Metwally Abdallah, Majda Alfakeer, Rasha N Felaly, Abdulaziz M. Almohyawi, Jabir H. Al-Fahemi, Salih S. Al-Juaid, Doaa F. Seyam, Elsayed M. Mabrouk, Kamal A. Soliman

“…Some chemical, electrochemical measurements, density functional theory and Monte Carlo simulations were utilized to study the adsorption behaviour and corrosion inhibition efficiency of m-TMPP and p-TMPP on the Cu (111) surface in acidic media. …”
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Robust Optimization of Planar Constrained Mechanical System with Varying Joint Clearance Size Based on Sensitivity Analysis by Yong Gao, Fang Zhang, Yuanyuan Li

“…The optimum values of design variables are determined by combining Monte Carlo sampling and multiobjective particle swarm optimization method. …”
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Artificial Neural Network-Based System for PET Volume Segmentation by Mhd Saeed Sharif, Maysam Abbod, Abbes Amira, Habib Zaidi

“…Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.…”
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A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…To minimize redundant information, we propose an improved Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm for selecting the optimal feature subset, ensuring both the efficiency and accuracy of fatigue recognition. …”
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Loan classification using a feed-forward neural network by U. I. Behunkou

“…The impact of data normalization on the final result was analyzed, the influence of the number of units in the hidden layer on the outcome was evaluated using a two-stage method and the Monte Carlo method, the effect of balanced data use was determined, the optimal threshold value for output layer of the neural network under investigation was calculated, the optimal activation function for the hidden layer units was found, the effect of increasing input indicators through missing values imputation and the use of polynomials of varying degrees was studied and the redundancy in the existing set of input indicators was analyzed.Conclusion. …”
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Uncertainty Evaluation of Stochastic Structural Response with Correlated Random Variables by Qiang Fu, Jianjun Liu, Jiarui Shi, Xiao Li, Xueji Cai, Zilong Meng

“…Several numerical examples with an engineering background involving correlated system parameter variables are analyzed and discussed under stochastic excitation, and their results are compared with those yielded by Monte Carlo simulation (MCS) so as to demonstrate the effectiveness of the approach proposed. …”
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Quantitative Risk Assessment of Vibrio parahaemolyticus Toxi Infection Associated with the Consumption of Roasted Shrimp (Penaeus monodon) by Arnaud Carter Keinko Takoundjou, Rhoda Nsen Bughe, Abraham Nkoue Tong, Sylvain Leroy Sado Kamdem, Jean Justin Essia-Ngang

“…Based on the distribution of total V. parahaemolyticus in shrimp and literature information indicating that nonhaemolysing carrier strains could be pathogenic to humans, the cooking, and consumption patterns, the daily exposure level generated in this study, and the dose-response model from other studies, the infectious risk was evaluated and quantified by the Monte Carlo simulation. This simulation was realized based on 10,000 iterations using the Model Risk software, version 4.0, in combination with Microsoft Excel. …”
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Discovering Large-scale Structure at 2 < z < 5 in the C3VO Survey by Denise Hung, Brian C. Lemaux, Olga Cucciati, Ben Forrest, Ekta A. Shah, Roy R. Gal, Finn Giddings, Derek Sikorski, Emmet Golden-Marx, Lori M. Lubin, Nimish Hathi, Giovanni Zamorani, Lu Shen, Sandro Bardelli, Letizia P. Cassarà, Gabriella De Lucia, Fabio Fontanot, Bianca Garilli, Lucia Guaita, Michaela Monika Hirschmann, Kyoung-Soo Lee, Andrew B. Newman, Vandana Ramakrishnan, Daniela Vergani, Lizhi Xie, Elena Zucca

“…As we previously accomplished with the ORELSE survey, we apply our technique known as Voronoi tessellation Monte Carlo (VMC) mapping to search for serendipitous galaxy overdensities at 2 <  z  < 5 in the three C3VO fields. …”
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ADeFS: A Deep Forest Regression-Based Model to Enhance the Performance Based on LASSO and Elastic Net by Zari Farhadi, Mohammad-Reza Feizi-Derakhshi, Israa Khalaf Salman Al-Tameemi, Wonjoon Kim

“…The proposed model is evaluated by Monte Carlo simulation and three real datasets. Findings demonstrate the superior performance of the proposed ADeFS-EN model over both gcforest and RF, as well as the combination of RF with shrinkage techniques.…”
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Simulation and Prediction of Injection Pressure in CO2 Geological Sequestration Based on Improved LSO Algorithm and BP Neural Networks by Miaomiao Liu, Xiaofei Fu, Shanpo Jia, Yongsheng Zhang, Yuying Zhang, Dan Yao

“…In order to avoid the occurrence of caprock integrity damage and gas escape due to injection pressure overrun in CO2 sequestration, an optimized back propagation (BP) neural network model based on Monte Carlo simulation (MCS) and an improved lion swarm optimization (ILSO) algorithm is proposed for the maximum sustainable injection pressure prediction. …”
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Estimation for Akshaya Failure Model with Competing Risks under Progressive Censoring Scheme with Analyzing of Thymic Lymphoma of Mice Application by Tahani A. Abushal, Jitendra Kumar, Abdisalam Hassan Muse, Ahlam H. Tolba

“…The Bayes estimate is obtained by using the Markov Chain Monte Carlo (MCMC) method under symmetric and asymmetric loss functions. …”
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Site-wise dynamic defects in a non-conserving exclusion process by Nikhil Bhatia, Arvind Kumar Gupta

“…Using a mean-field approach, we obtain an analytical expression for both particle and defect density and validate them using Monte Carlo simulation. The study investigates the steady-state characteristics of the system, including phase transitions, analysis of boundary layers, and phase diagrams. …”
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Multiple Gamma-Ray Detection Capability of a CeBr3 Detector for Gamma Spectroscopy by A. A. Naqvi, F. Z. Khiari, F. A. Liadi, Khateeb ur-Rehman, M. Raashid, A. A. Isab

“…The experimental results are in good agreement with Monte Carlo calculations. The study has shown excellent detection capabilities of the CeBr3 detector for eight prompt gamma rays over 517–8578 keV energy range without significant background interference.…”
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The Concept of Theoretical-Empirical Dualism in Teaching Math by G. D. Gefan

“…Particular attention is paid to the use of mathematical experiments in those frequent cases when it is necessary to replace or supplement complex evidence, illustrate new knowledge, and give research skills. Monte Carlo mathematical experiments are demonstrated, which serve, in particular, as a bright, figurative, and convincing form of reinforcing theoretical knowledge in the field of stochastic branches of mathematics. …”
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Magnetosphere-Ground Responses and Energy Spectra Analysis of Solar Proton Event on 28 October 2021 by Fang Zhang, Zhenxia Zhang, Dali Zhang, Xinqiao Li, Zhiqiang Ding, Lu Wang, Shujie Li, Zhenghua An, Jilong Zhang

“…By utilizing the Monte Carlo method to simulate the pile-up effect and accounting for the detector’s dead time, with the assistance of real-time incident counting rates, we successfully corrected the spectra in the 10–50 MeV range. …”
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Finite-Element-Based Time-Dependent Service Life Prediction for Carbonated Reinforced Concrete Aqueducts by Lan Zhang, Ri-Sheng He, Long-Wen Zhang, Yan-Ye Chen

“…Furthermore, the comparison with Monte Carlo simulation (MCS) results validates the high efficiency and accuracy of the proposed method, offering a valuable tool for addressing the reliability challenges of aqueducts exposed to carbonation and other environmental factors over time.…”
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Determining Parameters of Metal-Halide Perovskites Using Photoluminescence with Bayesian Inference by Manuel Kober-Czerny, Akash Dasgupta, Seongrok Seo, Florine M. Rombach, David P. McMeekin, Heon Jin, Henry J. Snaith

“…In this work, we demonstrate that time-resolved photoluminescence data of metal halide perovskites can be effectively evaluated by combining Bayesian inference with a Markov-chain Monte-Carlo algorithm and a physical model. This approach enables us to infer a high number of parameters that govern the performance of metal halide perovskite-based devices, alongside the probability distributions of those parameters, as well as correlations among all parameters. …”
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