CBM : online strategies on cost-aware buffer management for mobile video streaming by He, Jian, Xue, Zheng, Wu, Di, Wu, Oliver Dapeng, Wen, Yonggang

“…To this objective, we formulate the problem into a constrained stochastic optimization problem, and apply the Lyapunov optimization theory to derive the corresponding online strategy for cost minimization. …”
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Understanding agent-based models of financial markets : A bottom–up approach based on order parameters and phase diagrams by Lye, Ribin, Tan, James Peng Lung, Cheong, Siew Ann

“…Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.…”
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Advantages and learning for quantum modelling by Liu, Qing

“…Simulating stochastic processes using less resources is a key pursuit in many sciences. …”
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Data-driven prediction and impact analysis for smart city applications by Mo, Xiaoyun

“…Secondly, we develop a stochastic model to predict when and where a service delay or disruption may occur in rail systems. …”
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Prior geological knowledge enhanced Markov random field for development of geological cross-sections from sparse data by Qian, Zehang, Shi, Chao

“…The configuration is then integrated with the MRF algorithm for stochastic simulations of geological cross-sections. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

“…However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Simulation based decision support for airport landside capacity planning by Lim, Yi

“…However, some of these methods are too complicated to apply whereas the ones that are easy to apply often could not accurately model the stochastic and dynamic nature of an airport’s landside.…”
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Mendelian and non-Mendelian quadratic operators by Ganikhodjaev, Nasir, Saburov, Mansoor, Jamilov, Uygun

“…As an application of a non-Mendelian inheritance, we construct a quadratic stochastic operator that describes transmission of ABO and Rh blood groups.…”
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Long-range forecasting of the S&P stock market index using fractional integration techniques by Caporale, Guglielmo Maria, Gil-Alana, Luis A.

“…In this paper we examine the stochastic behaviour of the S&P 5000 stock market index by means of fractional integration techniques. …”
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Analysis of residuals in daily solar radiation time series by Sulaiman, Mohd Yusof, Win, Maw Hlaing Oo, Abdul Wahab, Mahdi, Sulaiman, Zainal Abidin

“…The deterministic annual component is obtained by Fourier analysis. The stochastic component of the time series is fitted to three models, ARMA (1,0), ARMA (2,0) and ARMA (1,1). …”
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Optimization of inventory distribution in clinical trial supply chain by Ng, Jasper Kang Tai

“…Due to the numerous uncertainties and decision making required in the clinical trial, a 2 stage stochastic programming was formed to minimise the operational cost. …”
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Development of data-driven controller for slosh suppression in liquid cargo vehicles by Mohd Falfazli, Mat Jusof, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Suid, Mohd Helmi, Saari, Mohd Mawardi

“…In addition, the performance of the SED based methods is compared to the other stochastic optimization based approaches, such as Simultaneous Perturbation Stochastic Approximation (SA) and Simulated Annealing (SA). …”
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Modeling issues in longevity and bonus-malus system by Tan, Chong It

“…We then propose two stochastic survival models for modeling the evolution of a hybrid survival curve. …”
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Implementation of the Algorithm Kalmah Filter on Reduction Model by Arif, Didik Khusnul, Widodo, Salmah, Apriliani, Erna

“…In this paper, the first will be establishment of a model reduction of dynamic stochastic discrete systems. Model reduction is done by cutting method equilibrium. …”
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A Gompertzian Model With Random Effects To Cervical Cancer Growth by Mazma Syahidatul Ayuni, Mazlan, Norhayati, Rosli

“…We apply 4-stage Runge- Kutta (SRK4) for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of the cervical cancer growth. …”
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On Dobrushin Ergodicity Coefficient and weak ergodicity of Markov Chains on Jordan Algebras by Mukhamedov, Farrukh

“…In this paper we study certain properties of Dobrushin's ergodicity coe�cient for stochastic operators de�ned on non-associative L1-spaces associated with semi-�nite JBW- algebras. …”
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Statistics for solving environmental problems by Elfaki, Faiz Ahmed Mohamed, Hadi, Agung Efriyo, Usman, Mustofa

“…Focus on specific aspects typically reduces a complex system into a simpler one described by stochastic or deterministic variables, in a trade-off between simplicity and accuracy. …”
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The evolution of Malaysian banking sector’s efficiency during financial duress: consequences, concerns, and policy implications by Sufian, Fadzlan

“…By employing the non-stochastic data envelopment analysis (DEA) method, the present paper provides empirical evidence on the efficiency of the Malaysian banking sector around the Asian financial crisis. …”
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Moment-closure Approximations to Levins Metapopulation Model by Krishnarajah, Isthrinayagy, Gibson, Gavin, Glenn, Marion

“…In this study, we apply the log-normal mixture and beta-binomial) mixture approximations to the stochastic version of the Levins metapopulation model. …”
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Evaluating premature convergence for metaheuristic. by Md Sultan, Abu Bakar, Abdullah, Azizol, Mahmod, Ramlan, Abdullah @ Selimun, Mohd Taufik

“…The evaluation of premature convergence rate is difficult to obtain because the stochastic nature of metaheuristic. This paper presents a statistical effort to evaluate and predict the premature rate and performance of metaheuristic. …”
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