The levelized cost of energy in the presence of uncertainty on the offshore wind speed by J. Pablo Arenas-López, Mohamed Badaoui

“…To carry out this task, we employ two techniques based on stochastic differential equations to generate wind power scenarios. …”
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Discrete-Time Retrial Queuing Systems with Last-Come-First-Served (LCFS) and First-Come-First-Served (FCFS) Disciplines: Negative Customer Impact and Stochastic Analysis by Iván Atencia-Mckillop, Sixto Sánchez-Merino, Inmaculada Fortes-Ruiz, José Luis Galán-García

“…Additionally, it is shown that the studied discrete-time system can approximate the M/G/1 continuous-time version of the model. …”
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The effect of positive interspike interval correlations on neuronal information transmission by Sven Blankenburg, Benjamin Lindner

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An application of queuing theory to SIS and SEIS epidemic models by Carlos M. Hernández-Suárez, Carlos Castillo-Chavez, Osval Montesinos López, Karla Hernández-Cuevas

“…In order to achieve this we first derive new approximations to quasistationary distribution (QSD) of SIS (Susceptible- Infected- Susceptible) and SEIS (Susceptible- Latent- Infected- Susceptible) stochastic epidemic models. …”
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Research on Performance of Covert Wireless Communication over Uplink LEO Satellite-Terrestrial Network by ZENG Shulei, CAO Bin

“…Specifically, by leveraging shot noise caused by ambient signals from terrestrial interferers, a terrestrial transmitter (Alice) can effectively obscure her signal from warden satellites. With the aid of stochastic geometry, the distributions of distances between the transmitter and satellites were analyzed, providing key insights into the uplink performance and interference experienced within a satellite's coverage area.Approximate expressions for the detection error probability and transmission outage probability were provided. …”
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Gauss-diffusion processes for modeling the dynamics of a couple of interacting neurons by Aniello Buonocore, Luigia Caputo, Enrica Pirozzi, Maria Francesca Carfora

“…Such an approximation is admissible for small instantaneous firing rates of both neurons.…”
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Hyperspectral Image Classification Using Spectral-Spatial Dual Random Fields With Gaussian and Markov Processes by Yaqiu Zhang, Lizhi Liu, Xinnian Yang

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SGD-TripleQNet: An Integrated Deep Reinforcement Learning Model for Vehicle Lane-Change Decision by Yang Liu, Tianxing Yang, Liwei Tian, Jianbiao Pei

“…This method integrates three types of deep Q-learning networks (DQN, DDQN, and Dueling DDQN) and uses the Stochastic Gradient Descent (SGD) optimization algorithm to dynamically adjust the network weights. …”
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Mitigation of Diffraction Effect in GNSS Positioning Considering Azimuth and PDOP in Canyon Environment by Qingfeng Wu, Xiaoya Wang, Houxiang Zhou

“…Experimental results show that the precision of the stochastic model based on equivalent elevation angles improves by approximately 24.25% after considering the threshold of azimuth angle. …”
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Predictive channel scheduling algorithm between macro base station and micro base station group by Yinghai XIE, Ruohe YAO, Bin WU

“…A novel predictive channel scheduling algorithm was proposed for non-real-time traffic transmission between macro-base stations and micro-base stations in 5G ultra-cellular networks.First,based on the stochastic stationary process characteristics of wireless channels between stationary communication agents,a discrete channel state probability space was established for the scheduling process from the perspective of classical probability theory,and the event domain was segmented.Then,the efficient scheduling of multi-user,multi-non-real-time services was realized by probability numerical calculation of each event domain.The theoretical analysis and simulation results show that the algorithm has low computational complexity.Compared with other classical scheduling algorithms,the new algorithm can optimize traffic transmission in a longer time dimension,approximate the maximum signal-to-noise ratio algorithm in throughput performance,and increase system throughput by about 14% under heavy load.At the same time,the new algorithm is accurate.Quantitative computation achieves a self-adaption match between the expected traffic rate and the actual scheduling rate.…”
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The Sum and Difference of Two Lognormal Random Variables by C. F. Lo

“…We have presented a new unified approach to model the dynamics of both the sum and difference of two correlated lognormal stochastic variables. By the Lie-Trotter operator splitting method, both the sum and difference are shown to follow a shifted lognormal stochastic process, and approximate probability distributions are determined in closed form. …”
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SOME PECULIAR FEATURES IN SHRINKAGE OF CLAY MASS DURING DRYING PROCESS by I. K. Ivanovsky, S. N. Osipov, L. V. Rafeenkova

“…The paper contains results of correlation and stochastic analysis for regularities in shrinkage of the Lukoml clay and molding mass prepared on its base, and also the Gloukhov and Gloukhovetsky kaolin and their mixtures.It has been revealed that an exponent is the most convenient approximation form of the shrinkage characteristic for the Lukoml clay and molding mass prepared on its base within significant range of moisture changes.After products’ molding in a vacuum press a linear dependence is considered as the most convenient type of approximation within the range of moisture changes and with the main shrinkage.…”
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Multivalued Impulsive SDEs Driven by G-Brownian Noise: Periodic Averaging Result by Mahmoud Abouagwa, Anas D. Khalaf, Nadia Gul, Sultan Alyobi, Al-Sharef Mohamed

“…This paper aims to study two approximation theorems in view of the periodic averaging results for non-Lipschitz multivalued stochastic differential equations with impulses and G-Brownian motion (MISDEGs). …”
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An Integrated Problem of p-Hub Location and Revenue Management with Multiple Capacity Levels under Disruptions by Yan-Ting Hou, Jia-Zhen Huo, Feng Chu

“…Furthermore, a sample average approximation approach is used for solving the stochastic programming formulation and a genetic algorithm approach is applied for both formulations. …”
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Helicopter Control Energy Reduction Using Moving Horizontal Tail by Tugrul Oktay, Firat Sal

“…Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). …”
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Adaptive Time-Stepping Using Control Theory for the Chemical Langevin Equation by Silvana Ilie, Monjur Morshed

“…Stochastic modeling of biochemical systems has been the subject of intense research in recent years due to the large number of important applications of these systems. …”
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The Holling Type II Population Model Subjected to Rapid Random Attacks of Predator by Jevgeņijs Carkovs, Jolanta Goldšteine, Kārlis Šadurskis

“…We present the analysis of a mathematical model of the dynamics of interacting predator and prey populations with the Holling type random trophic function under the assumption of random time interval passage between predator attacks on prey. We propose a stochastic approximation algorithm for quantitative analysis of the above model based on the probabilistic limit theorem. …”
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A Hardware Efficient Random Number Generator for Nonuniform Distributions with Arbitrary Precision by Christian de Schryver, Daniel Schmidt, Norbert Wehn, Elke Korn, Henning Marxen, Anton Kostiuk, Ralf Korn

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A New Gap Function for Vector Variational Inequalities with an Application by Hui-qiang Ma, Nan-jing Huang, Meng Wu, Donal O'Regan

“…We solve this optimization problem by employing the sample average approximation method. The convergence of optimal solutions of the approximation problems is also investigated.…”
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Application of Random Dynamic Grouping Simulation Algorithm in PE Teaching Evaluation by Haitao Hao

“…Finally, the application of the stochastic simulation evaluation model is illustrated by an example and compared with the absolute form evaluation. …”
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