Papers by Keyword: Markov Chain (MC)

Abstract: In this paper, a multiscale modeling approach has been developed to simulate the intergranular crack propagation in textured polycrystalline materials. Embedded Atom Method (EAM) and Molecular Dynamics (MD) simulations were carried out to determine the energy and fracture strength of different types of grain boundaries in Ni₃Al. Subsequently, the atomistic model has been integrated with the microstructure based model of crack propagation using the Voronoi-Markov Chain-Monte Carlo approach. The model has been utilized to evaluate the crack length for various scenarios and reasonable results are obtained.

Abstract: The life cycle performance indicator of construction engineering structure is the basic indicator of the core research indicator system of construction engineering life cycle. This paper has the reliability indicator of construction structure as a foundation, analyzes the general calculating methods of construction structure and reliable performance. On the other hand, it establishes prediction model of construction structure durability based on Markova chain, and introduces a practical case to analysis and test.

Abstract: ARL (Average Run Length) is used as a tool to measure the performance of control chart. But it isn’t very accurate. In this paper, a Markov chain method is proposed to calculate the APL (Average Product Length) of EWMA chart, and APL is used as a criterion of performance assessment to decide optimal design of this chart. By comparing with traditional EWMA design method, we can find that this method can detect little shifts in processes more quickly.

Abstract: In the practical engineering, to solve the small failure probabilities with correlated high-dimensional variables, the subset simulation (SS) is combined together with the Monte Carlo and importance sampling (IS) method. The samples from the probability density functions (PDF) of the importance sampling are used to construct the intermediate failure events, by which the small failure probabilities are turned into a Markov chain (MC), which is a continuous product made of a series large failure probability or conditional failure probability (CFP) which is easily answered, on which the structural reliability can be efficiently simulated by directly obtaining the samples with correlated ones. Finally, the 3 planet carriers of 3 grade planetary reducers in shield tunneling machine(STM) are as examples to check the algorithm above, the results show that the SS of the IS with correlated variables can highly simulate failure probability.

Abstract: The safety of the pipeline in use is tightly linked with the resident life and belongings. Reliable structural integrity and safety of gas pipelines under various service pressure events including defects should be warily evaluated. The reliability evaluation of gas pipelines is necessary to prevent risk. In this paper, Markov chain Monte Carlo is proposed to analyze the reliability of factors affecting gas pipeline operational condition in consideration of the character of historical data, the calculating processes of reliability prediction are provided in view of performance degradation characteristics of the factors.This paper takes corrosion as important factor affecting pipeline operation for example, calculates the reliability indexes of gas pipeline, studies the relation of failure rate and length/depth of corrosion pit ,operation time,etc. seeks weak links of system, and brings forward concrete and reliable measures to improve system reliability.

Abstract: Considering the grey feature of traffic accident occurrence, grey model optimized by least-square theory is introduced to prejudge the future trend of traffic accident. To improve the prediction precision of this model, an amendment factor of boundary value and Markov chain are proposed and the numerical application proves the effectiveness of this Grey –Markov predict model.

Abstract: Detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. In high-dimensional data, these approaches are bound to deteriorate due to the notorious “curse of dimensionality”. In this paper, we propose a novel approach named ODMC (Outlier Detection Based On Markov Chain)，the effects of the “curse of dimensionality” are alleviated compared to purely distance-based approaches. A main advantage of our new approach is that our method is to use a major feature of an undirected weighted graph to calculate the outlier degree of each node, In a thorough experimental evaluation, we compare ODMC to the ABOD and FindFPOF for various artificial and real data set and show ODMC to perform especially well on high-dimensional data.

Abstract: An image hided-data detection method is proposed combining 2-D Markov chain model and Support Vector Machines (SVM) by the paper, in which image pixels are predicted with their neighboring pixels, and the prediction-error image is generated by subtracting the prediction value from the pixel value. Support vector machines are utilized as classifier. As embedding data rate being 0.1 bpp, experimental investigation utilizing spread spectrum (SS) and a Quantization Index Modulation (QIM) method data hiding method respectively , correction detection rates are all above 90% . For optimum LSB method ,the method achieves a detection rate from 50% to 90% above with 0.01bpp-0.3bpp various embedding data rates.

Abstract: This paper deals with a system with elements with one element is the main element and the other elements are the spare parts of the main element. If one element fails, one of the spare parts starts working immediately. The failure rate of non working elements are zero and the failure rate of working element is time dependent as and the failed elements are not repairable. The system works until all elements failed. In the second part of this paper the differential equations between the state of the system are established and by solving this equation the reliability function of the system () is calculated. In the third part, a numerical example solved to determine the parameters of the system. Nomenclature The notations used in this paper are as follows: : Number of elements, : Failure rate of each element at time, : Probability that the system is in state with spare element at time, : Probability that system works at time, : Mean time to failure of the system,

Abstract: This article presents a proper approach for the prediction of output power for photovoltaic generation system. Using the results of solar irradiation from the sunny-day-model as the base value, which are accurate when the sky is clear, and correcting the forecasting results with the assistance of Markov Chain in order to make them valid for other kinds of weathers. To be specific, by utilizing Markov Chain, the underlying stochastic effects of clouds coverage can be minimized and thus harvest more accurate results. The method is tested on the photovoltaic generation system of Electrical Engineering School, Wuhan University, P.R.China and rendered a satisfactory precision of forecasting. Finally, further measurements for enhancing accuracy are also discussed in this paper.