Design of Super Resolution and Fuzzy Deep Learning Architecture for the Classification of Land Cover and Landsliding Using Aerial Remote Sensing Data by Junaid Ali Khan, Muhammad Attique Khan, Mohammed Al-Khalidi, Dina Abdulaziz AlHammadi, Areej Alasiry, Mehrez Marzougui, Yudong Zhang, Faheem Khan

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Statistical Timing Analysis for Subthreshold Circuit Based on Bayesian Inference by Donglin Liu, Yuping Wu, Zhiqiang Li, Xuelian Zhang, Xi Tian

“…The most accurate delay prediction method is Monte Carlo simulation. To obtain accurate estimates, a large number of Monte Carlo simulations are often required, with the consideration of process changes, which is not feasible in large circuits. …”
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Design and Simulation of a New Model for Treatment by NCT by Seyed Alireza Mousavi Shirazi, Dariush Sardari

“…The neutron flux and the deposited dose in the all components and different layers of the mentioned phantom are computed by Monte Carlo simulation. The results of Monte Carlo method are compared with analytical method results so that by using a computer program in Turbo-Pascal programming, the deposited dose in the liver phantom has been computed.…”
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Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems by Maria Chiara Angelini, Angelo Giorgio Cavaliere, Raffaele Marino, Federico Ricci-Tersenghi

“…Abstract Is Stochastic Gradient Descent (SGD) substantially different from Metropolis Monte Carlo dynamics? This is a fundamental question at the time of understanding the most used training algorithm in the field of Machine Learning, but it received no answer until now. …”
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Statistical mechanics and machine learning of the α-Rényi ensemble by Andrew Jreissaty, Juan Carrasquilla

“…Next, we re-introduce correlations and consider the model in one and two dimensions, presenting analytical arguments for the former and devising a Monte Carlo approach to the study of the latter. Remarkably, we find that while mean-field predicts a continuous phase transition below a threshold index value of α∼1.303 and a first-order transition above it, the Monte Carlo results in two dimensions point to a continuous transition at all α. …”
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Improved node localization algorithm for wireless sensor network by ZENG Fan-zi, SUN Zheng-zhang, LUO Juan, LI Ren-fa

“…An location algorithm called MCBN（Monte Carlo localization boxed using non-anchor） was proposed, which is based on the Monte Carlo localization algorithm. …”
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Stochastic modeling of structural fatigue damage in High Strength Steel structures by Jiri Brozovsky, Martin Krejsa, Petr Lehner, Premysl Parenica, Stanislav Seitl

“…This method can be used as an alternative to Monte Carlo � based approaches for problems of structural reliability. …”
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Application of RQMC for CDO Pricing with Stochastic Correlations under Nonhomogeneous Assumptions by Shuanghong Qu, Lingxian Meng, Hua Li

“…The simulation results of RQMC and Monte Carlo (MC) method were compared from the perspective of variance changes. …”
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Adsorption of Lennard-Jones Fluids in Carbon Slit Pores of a Finite Length. A Computer Simulation Study by A. Wongkoblap, S. Junpirom, D.D. Do

“…The effects of the number of cycles necessary to reach equilibrium, the initial allocation of particles, the displacement step and the simulation box size were particularly investigated in the Monte Carlo simulation with Canonical Ensembles. Of these parameters, the displacement step had the most significant effect on the performance of the Monte Carlo simulation. …”
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The Ghent Hybrid model in NuWro: a new neutrino single-pion production model in the GeV regime by Qiyu Yan, Kajetan Niewczas, Alexis Nikolakopoulos, Raúl González-Jiménez, Natalie Jachowicz, Xianguo Lu, Jan Sobczyk, Yangheng Zheng

“…Frameworks of oscillation analyses strongly rely on Monte Carlo neutrino event generators, which provide theoretical predictions of neutrino interactions on nuclear targets. …”
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Asymmetric Randomly Censored Mortality Distribution: Bayesian Framework and Parametric Bootstrap with Application to COVID-19 Data by Rashad M. EL-Sagheer, Mohamed S. Eliwa, Khaled M. Alqahtani, Mahmoud EL-Morshedy

“…In Bayesian framework, the Bayes estimates of the unknown parameters are evaluated by applying the Markov chain Monte Carlo technique, and highest posterior density credible intervals are also carried out. …”
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Block Markov superposition transmission over turbulence channels in outdoor optical wireless communication by Jin-shun ZHU, Xiao MA

“…Based on the equivalent genie-aided system,the bit-error rate of the block Markov superposition transmission system was analyzed and the union bound of the bit-error rate of the genie-aided system was derived.When the bit-error rate was extremely low at which the Monte Carlo simulation was time-consuming,the union bound could be adopted to evaluate the performance of the block Markov superposition transmission system.Simulations under turbulence conditions from weak to strong are performed which show that,in the low bit-error rate region,performance of the block Markov superposition transmission system matches well with the lower bound.It is also illustrated that the derived union bound matches well with Monte Carlo simulation result.At the BER of 10^-5,block Markov superposition transmission system with transmission memory 2 performs within 1 dB away from the Shannon limit.…”
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Novel Strategy to Improve the Performance of Localization in WSN by M. Vasim Babu, A. V. Ramprasad

“…A novel strategy of discrete energy consumption model for WSN based on quasi Monte Carlo and crude Monte Carlo method is developed. …”
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Stochastic Finite Element Simulation of Uncertain Structures Subjected to Earthquake by Subrata Chakraborty, Santi Sekhar Dey

“…The basic objective is to investigate the possibility of applying the Neumann expansion technique coupled with the Monte Carlo simulation for dynamic stochastic systems upto that extent of parameter variation after which the method is no longer gives accurate results compared to that of the direct Monte carlo simulation. …”
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Sign Problem in Tensor-Network Contraction by Jielun Chen, Jiaqing Jiang, Dominik Hangleiter, Norbert Schuch

“…First, we consider contraction via Monte Carlo sampling and find that the transition from hard to easy occurs when the tensor entries become predominantly positive; this can be understood as a tensor-network manifestation of the well-known negative-sign problem in quantum Monte Carlo. …”
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Bayesian and non-bayesian analysis for stress-strength model based on progressively first failure censoring with applications. by Salem A Alyami, Amal S Hassan, Ibrahim Elbatal, Olayan Albalawi, Mohammed Elgarhy, Ahmed R El-Saeed

“…To evaluate the effectiveness of the several estimators created, a Monte Carlo numerical analysis is also carried out. …”
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Novel Complete Probabilistic Models of Random Variation in High Frequency Performance of Nanoscale MOSFET by Rawid Banchuin

“…The proposed models have been verified based on the 65 nm CMOS technology by using the Monte-Carlo SPICE simulations of benchmark circuits and Kolmogorov-Smirnov tests as highly accurate since they fit the Monte-Carlo-based analysis results with 99% confidence. …”
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Resummed jet mass distribution with trimming in Z+jet events at the LHC by Safa Gaid, Yazid Delenda, Rachik Soualah

“…Our resummed result is compared to Monte Carlo parton shower simulations from Pythia 8, Herwig++ and Sherpa 2 event generators.…”
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Safe use of jet pull by Andrew Larkoski, Simone Marzani, Chang Wu

“…Furthermore, because of their sensitivity to wide-angle soft radiation, we anticipate that these asymmetries can play an important role in assessing subleading colour correlations and their modelling in general-purpose Monte Carlo parton showers.…”
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Bayesian Estimation and Prediction for Flexible Weibull Model under Type-II Censoring Scheme by Sanjay Kumar Singh, Umesh Singh, Vikas Kumar Sharma

“…Since the predictive posteriors are not in the closed form, we proposed to use the Monte Carlo Markov chain (MCMC) methods to approximate the posteriors of interest. …”
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