Results 11 to 20 of about 555,552 (274)

Numerical simulations for stochastic meme epidemic model

Advances in Difference Equations, 2020
The primary purpose of this study is to perform the comparison of deterministic and stochastic modeling. The effect of threshold number is also observed in this model.
Ali Raza, Muhammad Rafiq, Dumitru Baleanu, Muhammad Shoaib Arif   +3 more
doaj   +1 more source

Design of nonstandard computational method for stochastic susceptible–infected–treated–recovered dynamics of coronavirus model

Advances in Difference Equations, 2020
The current effort is devoted to investigating and exploring the stochastic nonlinear mathematical pandemic model to describe the dynamics of the novel coronavirus.
Wasfi Shatanawi, Ali Raza, Muhammad Shoaib Arif, Kamaledin Abodayeh, Muhammad Rafiq, Mairaj Bibi   +5 more
doaj   +1 more source

A New Stochastic Process of Prestack Inversion for Rock Property Estimation

Applied Sciences, 2022
In order to enrich the current prestack stochastic inversion theory, we propose a prestack stochastic inversion method based on adaptive particle swarm optimization combined with Markov chain Monte Carlo (MCMC).
Long Yin, Sheng Zhang, Kun Xiang, Yongqiang Ma, Yongzhen Ji, Ke Chen, Dongyu Zheng   +6 more
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Effects of Probability Function on the Performance of Stochastic Programming [PDF]

Journal of Optimization in Industrial Engineering, 2018
Stochastic programming is a valuable optimization tool where used when some or all of the design parameters of an optimization problem are defined by stochastic variables rather than by deterministic quantities.
Mohammad Ebrahim Karbaschi, Mohammad Reza Banan   +1 more
doaj   +1 more source

Stochastic optimization for the scheduling of a grid-connected microgrid with a hybrid energy storage system considering multiple uncertainties

Energy Reports, 2022
The deployment of a microgrid with renewable energy sources (RESs) generally considers two aspects i.e., the need for the energy storage and the presence of many uncertainties due to the intermittent nature of several RESs and the load demand variability.
Firmansyah Nur Budiman, Makbul A.M. Ramli, Ahmad H. Milyani, Houssem R.E.H. Bouchekara, Muhyaddin Rawa, Rifqi Firmansyah Muktiadji, Mustafa M.A. Seedahmed   +6 more
doaj   +1 more source

Quantitative Stability of Optimization Problems with Stochastic Constraints

Mathematics, 2023
In this paper, we consider optimization problems with stochastic constraints. We derive quantitative stability results for the optimal value function, the optimal solution set and the feasible solution set of optimization models in which the underlying ...
Wei Ouyang, Kui Mei
doaj   +1 more source

A Stochastic Multiobjective Optimization Framework for Wireless Sensor Networks

EURASIP Journal on Wireless Communications and Networking, 2010
In wireless sensor networks (WSNs), there generally exist many different objective functions to be optimized. In this paper, we propose a stochastic multiobjective optimization approach to solve such kind of problem.
Shibo He, Jiming Chen, Weiqiang Xu, Youxian Sun, Preetha Thulasiraman, Xuemin (Sherman) Shen   +5 more
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Numerical techniques for stochastic foot and mouth disease epidemic model with the impact of vaccination

Advances in Difference Equations, 2020
The spread of an epidemic diseases is stochastic in nature. It is more realistic to include this stochasticity when modelling the dynamics of a communicable disease.
Kamaleldin Abodayeh, Muhammad Shoaib Arif, Ali Raza, Muhammad Rafiq, Mairaj Bibi, Amna Nazeer   +5 more
doaj   +1 more source

Gray Image Denoising Based on Array Stochastic Resonance and Improved Whale Optimization Algorithm

Applied Sciences, 2022
Aiming at the poor effect of traditional denoising algorithms on image enhancement with strong noise, an image denoising algorithm based on improved whale optimization algorithm and parameter adaptive array stochastic resonance is proposed in the paper ...
Weichao Huang, Ganggang Zhang, Shangbin Jiao, Jing Wang   +3 more
doaj   +1 more source

Optimal Stochastic Planarization [PDF]

2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 2010
It has been shown by Indyk and Sidiropoulos [IS07] that any graph of genus g>0 can be stochastically embedded into a distribution over planar graphs with distortion 2^O(g). This bound was later improved to O(g^2) by Borradaile, Lee and Sidiropoulos [BLS09]. We give an embedding with distortion O(log g), which is asymptotically optimal.
openaire   +2 more sources