Stochastic Research Articles

A Stochastic Model of Changes in the Operational States of Means of Transport

A Stochastic Model of Changes in the Operational States of Means of Transport

Correction: Effects of dry period length on production, cash flows and greenhouse gas emissions of the dairy herd: A dynamic stochastic simulation model.

[This corrects the article DOI: 10.1371/journal.pone.0187101.].

On the Equivalence of Stochastic Fixed Point Iterations for Generalized φ-Contractive-Like Operators

We present the equivalence of some stochastic fixed point iterative algorithms by proving the equivalence between the convergence of random implicit Jungck-Kirk-multistep, random implicit Jungck-Kirk-Noor, random implicit Jungck-Kirk-Ishikawa, and random implicit Jungck-Kirk-Mann iterative algorithms for generalized φ-contractive-like random operators defined on separable Banach spaces.

Seismic fragility assessment of isolated structures by using stochastic response database

The seismic isolation system makes a structure isolated from ground motions to protect the structure from seismic events. Seismic isolation techniques have been implemented in full-scale buildings and bridges because of their simplicity, economic effectiveness, inherent stability and reliability. As for the responses of an isolated structure due to seismic events, it is well known that the most uncertain aspects are the seismic loading itself and structural properties. Due to the randomness of earthquakes and uncertainty of structures, seismic response distributions of an isolated structure are needed when evaluating the seismic fragility assessment (or probabilistic seismic safety assessment) of an isolated structure. Seismic response time histories are useful and often essential elements in its design or evaluation stage. Thus, a large number of non-linear dynamic analyses should be performed to evaluate the seismic performance of an isolated structure. However, it is a monumental task to gather the design or evaluation information of the isolated structure from too many seismic analyses, which is impractical. In this paper, a new methodology that can evaluate the seismic fragility assessment of an isolated structure is proposed by using stochastic response database, which is a device that can estimate the seismic response distributions of an isolated structure without any seismic response analyses. The seismic fragility assessment of the isolated nuclear power plant is performed using the proposed methodology. The proposed methodology is able to evaluate the seismic performance of isolated structures effectively and reduce the computational efforts tremendously.

Davie’s type uniqueness for a class of SDEs with jumps

Un résultat de A.M. Davie (Int. Math. Res. Not. 24 (2007) rnm124) établit qu’une équation stochastique multi-dimensionnelle $dX_{t}=b(t,X_{t})\,dt+dW_{t}$, $X_{0}=x$, dirigée par un processus de Wiener $W=(W_{t})$ avec un coefficient $b$ qui est seulement borné et mesurable admet une unique solution pour presque tout choix de la trajectoire du processus $W$ la dirigeant. Nous considérons un problème similaire lorsque $W$ est remplacé par un processus de Lévy $L=(L_{t})$ et $b$ est $\beta$-Hölder continu en espace. Nous supposons que $L_{1}$ a un moment fini d’ordre $\theta$ pour un certain $\theta>0$. En utilisant un nouveau résultat de régularité càdlàg, nous prouvons que l’existence et unicité forte pour l’EDS, associées à une $L^{p}$-Lipschitz continuité de la solution forte par rapport à $x$, impliquent une unicité de type Davie pour presque tout choix de la trajectoire de Lévy. Nous appliquons ce résultat à une classe d’EDS dirigées par un processus de Lévy $\alpha$-stable non dégénéré pour $\alpha\in(0,2)$ et $\beta>1-\alpha/2$.

Survey of resident behaviour related to air conditioner operation in low-cost apartments of kuala lumpur

Predictions of air conditioner (AC) use can greatly facilitate efforts to increase energy efficiency in buildings and promote sustainability. In order to determine the statistical characteristics of occupant behaviour related to AC operation, a series of surveys were conducted between September 2013 and December 2015 in 63 dwellings within two apartments in Kuala Lumpur, Malaysia. Measurements were taken either in the bedroom or living room of each dwelling. The results indicate that occupants who use ACs more frequently tend to use them for longer periods. It was found that AC use in bedrooms is not affected by outdoor temperature but is controlled by the habitual behaviour of the occupant. AC usage in living rooms slightly increases with increases in outdoor temperature. AC usage predominantly occurs at night time, with a maximum of 50 % of occupants using ACs in bedrooms. The start time and duration of use vary for each dwelling. These findings on stochastic resident behaviour might be useful for various building energy simulations in predicting realistic AC loads, particularly in tropical climates.

Optimal Sizing of Energy Storage System for Wind Farms Combining Stochastic Programming and Sequential Monte Carlo Simulation

Optimal Sizing of Energy Storage System for Wind Farms Combining Stochastic Programming and Sequential Monte Carlo Simulation

Retracted: Reliability assessment of composite generation expansion planning considering wind turbine

The expansion planning of wind turbine generating (WTG) requires the information of its forced outage rate (FOR) determined by using the continuous-time Markov Chain. In contrast with the conventional power plant, for the case study of WTG, the determination of FOR is utterly unique since it depends on the information of uncertain weather condition. Hence, the loss of load expectation (LOLE) and expected unserved energy (EUE) could be estimated so that it will not infringe its respective predetermined limits indispensable for the expansion planning of WTG using the stochastic approach. The modified IEEE RTS-79 system is used as a case study to verify effectiveness of the proposed method in the determination of WTG expansion planning. The results have shown improvement on the EUE and LOLE in relation with optimal expansion of the WTG units determined by using the proposed method.

Study of buffer effects on the grouping efficacy measure of stochastic cell formation problem

Study of buffer effects on the grouping efficacy measure of stochastic cell formation problem

Comparison study on LES combustion models in diffusion flame

This study comparatively analyzes the calculation performances of different large-eddy simulation (LES) combustion models in a diffused flame simulation to investigate the performances of different LES-turbulent combustion models. The flamelet/progress variable (FPV), partially stirred reactor (PaSR), and transport joint possibility density function (PDF) combustion model are adopted to perform a numerical simulation analysis for Flame D in the Sandia Lab. The comparison between the calculation results and the test data shows that the three models can properly simulate the diffused flame. The transport PDF model based on the Eulerian stochastic field method can realize better results, especially the forecast for the intermediate radicals (OH) and the pollutant emissions (NO). However, the calculation volume is huge. The calculation speed and precision of PaSR are acceptable. The FPV method can save much CPU time, and has great value in engineering applications. (Less)

Optimal Inventory-allocation Integrated Model for Perishable Items with Stochastic Demand in a Single-vendor Multi-retailer Supply Chain

This study investigates an increasingly widespread supply chain system that involves a vendor cyclically supplying specific perishable item to multiple retailers. In general, the vendor has to earlier and accurately determine inventory quantity to meet aggregate demand, and exactly allocate the inventory among a number of retailers to reduce the adjustment costs. Meanwhile, a vital challenge faced for vendors is to develop an efficient inventory- allocation decision model for given perishable item with stochastic and correlated retailer demands during upcoming selling period. To this end, an effective and practical analytical approach, which extends the newsvendor model to incorporate the considered inventory- allocation decision, is proposed here to simultaneously solve the optimal inventory quantity and allocation policy for maximizing expected vendor profits of perishable items. Especially, the lognormal distribution and Ito process is used here to model the behaviors of individual demand shift. Also, an effective integrated approach is presented to work out the aggre- gate demand during next selling period. Finally, numerical experiments are conducted to demonstrate and validate the proposed model and extract the valuable managerial findings.

Pathwise stochastic calculus with local times

Nous etudions la notion de temps local pour un processus continu, defini comme la limite de fonctions discretes le long d’une suite de partitions de l’intervalle de temps. Notre approche englobe les definitions deja existantes et coincide p.s. avec la definition (stochastique) usuelle des temps locaux pour les trajectoires de semimartingales continues. Nous etablissons une version trajectorielle des formules de changement de variables, de temps et de Tanaka–Meyer ansi que plusieures conditions equivalentes pour l’existence du temps local trajectoire par trajectoire. Finalement, nous proposons une etude detaillee de la facon dont le processus limite, son temps local et sa variation quadratique, dependent du choix de la suite de partitions. Nous montrons en particulier qu’un processus non-decroissant donne peut toujours etre obtenu p.s. comme la variation quadratique d’un mouvement Brownien standard le long d’une suite appropriee de partitions (aleatoires). De tels comportements pathologiques sont cependant exclus quand les partitions sont construites a l’aide de temps d’arret.

Stochastic optimization method based on improved cross entropy

Stochastic optimization method based on improved cross entropy

A Three-Parameter Lindley Distribution

A three-parameter Lindley distribution, which includes some two-parameter Lindley distributions introduced by Shanker and Mishra (2013 a, 2013 b), Shanker et al (2013), Shanker and Amanuel (2013), two-parameter gamma distribution, and one parameter exponential and Lindley distributions as special cases, has been proposed for modeling lifetime data. Its statistical properties including its shape, moments, skewness, kurtosis, hazard rate function, mean residual life function, stochastic ordering, mean deviations, order statistics, Renyi entropy measure, Bonferroni and Lorenz curves, stress-strength reliability have been discussed. For estimating its parameters, maximum likelihood estimation has been discussed. Finally, a numerical example has been presented to test the goodness of fit of the proposed distribution and the fit has been compared with the three-parameter generalized Lindley distribution.

Synchronization control of cyber physical systems during malicious stochastic attacks

Synchronization control of cyber physical systems during malicious stochastic attacks

A restricted B-spline estimation of diffusion processes with applications to financial data

Time-homogeneous diffusion process plays an important role in the financial market, and it is widely used for describing the stochastic dynamics of the underlying economic variables. In this work, we study nonparametric estimation of the drift and diffusion functions for the time-homogeneous diffusion process, and propose a new nonparametric regression technique based on higher-order approximations, which is called B-spline approach. The nonnegativity of the diffusion function is guaranteed by the restricted B-spline method. Our simulation results show that our method indeed outperforms the local polynomial method.

Modeling Robotic Cell and Analyzing the Influences of Stochastic Factors

Modeling Robotic Cell and Analyzing the Influences of Stochastic Factors

Comparison Performance Evaluation of Modified Genetic Algorithm and Modified Counter Propagation Network for Online Character Recognition

This paper carries out performance evaluation of a Modified Genetic Algorithm (MGA) and Modified Counter Propagation Network (MCPN) Network for online character recognition. Two techniques were used to train the feature vectors using supervised and unsupervised methods. First, the modified genetic algorithm used feature selection to filter irrelevant features vectors and improve character recognition because of its stochastic nature. Second, MCPN has its capability to extract statistical properties of the input data. MGA and MCPN techniques were used as classifiers for online character recognition then evaluated using 6200-character images for training and testing with best selected similarity threshold value. The experimental results of evaluation showed that, at 5 x 7 pixels, MGA had 97.89% recognition accuracy with training time of 61.20ms while MCPN gave 97.44% recognition accuracy in a time of 62.46ms achieved. At 2480, MGA had 96.67% with a training time of 4.53ms, whereas MCPN had 96.33% accuracy with a time of 4.98ms achieved. Furthermore, at 1240 database sizes, MGA has 96.44 % recognition accuracy with 0.62ms training time whereas MCPN gave 96.11% accuracy with 0.75ms training time. The two techniques were evaluated using different performance metrics. The results suggested the superior nature of the MGA technique in terms of epoch, recognition accuracy, convergence time, training time and sensitivity.

Bayesian Inference for Stochastic Copula Models

We proposes a new Bayesian MCMC algorithm for dynamic stochastic copula models with dependence parameters as unobserved state variables and presents the performance of the proposed MCMC algorithm through simulations. Our MCMC algorithm draws the state variables with an acceptancerejection Metropolis-Hastings algorithm using the candidate generating probability density function obtained by approximating the probability density function of the observed variables to the normal distribution of the dependence parameter.As an empirical example,weanalyzedthe stochasticcopulamodels for the KOSPI index and the HSCE index (Hang Seng China enterprise index) returnsfromJanuary3,2003toDecember30,2014usingtheproposedalgorithm. The Bayesian inference and model comparison results of the stochastic copula models of Gaussian copula, Student t-copula, Clayton copula, Frank copula, rotated Gumbel copula, and Plackett copula showed that Student t-copula model couldbeselectedasthebestmodel.Thesemodelcomparisonsresultsimplythat even though Gaussian stochastic copula model can capture ��near asymptotic dependence��, there may exist extreme tail dependence that can not be captured by the Gaussian stochastic copula model.

Roof failure of shallow tunnel based on simplified stochastic medium theory

The failure mechanism of tunnel roof is investigated with upper bound theorem of limit analysis. The stochastic settlement and nonlinear failure criterion are considered in the present analysis. For the collapse of tunnel roof, the surface settlement is estimated by the simplified stochastic medium theory. The failure curve expressions of collapse blocks in homogeneous and in layered soils are derived, and the effects of material parameters on the potential range of failure mechanisms are discussed. The results show that the material parameters of initial cohesion, nonlinear coefficient and unit weight have significant influences on the potential range of collapse block in homogeneous media. The proportion of collapse block increases as the initial cohesion increases, while decreases as the nonlinear coefficient and the unit weight increase. The ground surface settlement increases with the tunnel radius increasing, while the possible collapse proportion decreases with increase of the tunnel radius. In layered stratum, the study is investigated to analyze the effects of material parameters of different layered media on the proportion of possible collapse block.