Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other ...Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.展开更多
For some products,degradation mechanisms change during testing,and therefore,their degradation patterns vary at different points in time;these points are called change-points.Owing to the limitation of measurement cos...For some products,degradation mechanisms change during testing,and therefore,their degradation patterns vary at different points in time;these points are called change-points.Owing to the limitation of measurement costs,time intervals for degradation measurements are usually very long,and thus,the value of change-points cannot be determined.Conventionally,a certain degradation measurement is selected as the change-point in a two-phase degradation process.According to the tendency of the two-phase degradation process,the change-point is probably located in the interval between two neighboring degradation measurements,and it is a fuzzy variable.The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results.In this paper,based on the fuzzy theory,a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed.First,a two-phase Wiener degradation model is developed according to the membership function of the change-point.Second,the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach.Finally,the proposed methodology is verified via a case study.The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.展开更多
A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc....A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc. The availability of the system is discussed by using Markov renewal theory, Laplace transform and probability analysis methods. A numerical example is given to illustrate the results obtained in the paper.展开更多
Let Q be the Q-matrix of an irreducible, positive recurrent Markov process on a countable state space. We show that, under a number of conditions, the stationary distributions of the n × n north-west corner augme...Let Q be the Q-matrix of an irreducible, positive recurrent Markov process on a countable state space. We show that, under a number of conditions, the stationary distributions of the n × n north-west corner augmentations of Q converge in total variation to the stationary distribution of the process. Two conditions guaranteeing such convergence include exponential ergodicity and stochastic monotonicity of the process. The same also holds for processes dominated by a stochastically monotone Markov process. In addition, we shall show that finite perturbations of stochastically monotone processes may be viewed as being dominated by a stochastically monotone process, thus extending the scope of these results to a larger class of processes. Consequently, the augmentation method provides an attractive, intuitive method for approximating the stationary distributions of a large class of Markov processes on countably infinite state spaces from a finite amount of known information.展开更多
At first, the concept of bridge reliability is given, followed with its mathematic model. Then, based on the analysis about the mechanism of the damage and repair of bridges, and the state diversion of bridge network,...At first, the concept of bridge reliability is given, followed with its mathematic model. Then, based on the analysis about the mechanism of the damage and repair of bridges, and the state diversion of bridge network, the state diversion process is proved to be birth-and-death process. In the end, the state diversion balance equation of bridge network is built, and the evaluation model of wartime bridge reliability is got. The model is used in a certain example, and it is proved to be precise and credible.展开更多
Aviation and aerospace system are typical Phased-Mission Systems(PMSs)featured with varying configuration,phased load condition and cross phase failure correlation.The coupling effect of Functional Dependency(FDEP)and...Aviation and aerospace system are typical Phased-Mission Systems(PMSs)featured with varying configuration,phased load condition and cross phase failure correlation.The coupling effect of Functional Dependency(FDEP)and Physical Dependency(PDEP)has a unique influence on the failure behavior of PMS.In this article,the coupling effect is analyzed,and the degradation of components is modeled with the positive drift wiener process,in which the drift coefficient is related to environmental conditions and operation stress.Finally,failure behavior and system reliability are simulated.An avionics controller is studied as a case,with the degradation time distribution model and simulation algorithm,the coupling effect and dynamical system reliability can be achieved.Results show that this modeling method can describe the coupling effects of FDEP and PDEP and their influence on the failure behavior and reliability of the PMS system.展开更多
Gearbox in offshore wind turbines is a component with the highest failure rates during operation. Analysis of gearbox repair policy that includes economic considerations is important for the effective operation of off...Gearbox in offshore wind turbines is a component with the highest failure rates during operation. Analysis of gearbox repair policy that includes economic considerations is important for the effective operation of offshore wind farms. From their initial perfect working states, gearboxes degrade with time, which leads to decreased working efficiency. Thus, offshore wind turbine gearboxes can be considered to be multi-state systems with the various levels of productivity for different working states. To efficiently compute the time-dependent distribution of this multi-state system and analyze its reliability, application of the nonhomogeneous continuous-time Markov process(NHCTMP) is appropriate for this type of object. To determine the relationship between operation time and maintenance cost, many factors must be taken into account, including maintenance processes and vessel requirements. Finally, an optimal repair policy can be formulated based on this relationship.展开更多
In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system ...In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.展开更多
In this article, we summarize some results on invariant non-homogeneous and dynamic-equilibrium (DE) continuous Markov stochastic processes. Moreover, we discuss a few examples and consider a new application of DE pro...In this article, we summarize some results on invariant non-homogeneous and dynamic-equilibrium (DE) continuous Markov stochastic processes. Moreover, we discuss a few examples and consider a new application of DE processes to elements of survival analysis. These elements concern the stochastic quadratic-hazard-rate model, for which our work 1) generalizes the reading of its It? stochastic ordinary differential equation (ISODE) for the hazard-rate-driving independent (HRDI) variables, 2) specifies key properties of the hazard-rate function, and in particular, reveals that the baseline value of the HRDI variables is the expectation of the DE solution of the ISODE, 3) suggests practical settings for obtaining multi-dimensional probability densities necessary for consistent and systematic reconstruction of missing data by Gibbs sampling and 4) further develops the corresponding line of modeling. The resulting advantages are emphasized in connection with the framework of clinical trials of chronic obstructive pulmonary disease (COPD) where we propose the use of an endpoint reflecting the narrowing of airways. This endpoint is based on a fairly compact geometric model that quantifies the course of the obstruction, shows how it is associated with the hazard rate, and clarifies why it is life-threatening. The work also suggests a few directions for future research.展开更多
This paper proposes reliability and maintenance models for systems suffering random shocks arriving according to a non-homogeneous Poisson process.The system degradation process include two stages:from the installatio...This paper proposes reliability and maintenance models for systems suffering random shocks arriving according to a non-homogeneous Poisson process.The system degradation process include two stages:from the installation of a new system to an initial point of a defect(normal stage),and then from that point to failure(defective stage),following the delay time concept.By employing the virtual age method,the impact of external shocks on the system degradation process is characterized by random virtual age increment in the two stages,resulting in the corresponding two-stage virtual age process.When operating in the defective state,the system becomes more susceptible to fatigue and suffers from a greater aging rate.Replacement is carried out either on failure or on the detection of a defective state at periodic or opportunistic inspections.This paper evaluates system reliability performance and investigates the optimal opportunistic maintenance policy.A case study on a cooling system is given to verify the obtained results.展开更多
I. INTRODUCTION AND DEFINITIONS In this report, we shall give a simple counterexample to negative Theorem 1 and Proposition 3 (c)(ii)in [1] and explain the difference between the large-past Markov property and *-Marko...I. INTRODUCTION AND DEFINITIONS In this report, we shall give a simple counterexample to negative Theorem 1 and Proposition 3 (c)(ii)in [1] and explain the difference between the large-past Markov property and *-Markov property. Thereby some mistakes are cleared up.展开更多
This paper contributes to the structural reliability problem by presenting a novel approach that enables for identification of stochastic oscillatory processes as a critical input for given mechanical models. Identifi...This paper contributes to the structural reliability problem by presenting a novel approach that enables for identification of stochastic oscillatory processes as a critical input for given mechanical models. Identification development follows a transparent image processing paradigm completely independent of state-of-the-art structural dynamics, aiming at delivering a simple and wide purpose method. Validation of the proposed importance sampling strategy is based on multi-scale clusters of realizations of digitally generated non-stationary stochastic processes. Good agreement with the reference pure Monte Carlo results indicates a significant potential in reducing the computational task of first passage probabilities estimation, an important feature in the field of e.g., probabilistic seismic design or risk assessment generally.展开更多
Compared with the classical Markov repairable system, the Markov repairable system with stochastic regimes switching introduced in the paper provides a more realistic description of the practical system. The system ca...Compared with the classical Markov repairable system, the Markov repairable system with stochastic regimes switching introduced in the paper provides a more realistic description of the practical system. The system can be used to model the dynamics of a repairable system whose performance regimes switch according to the external conditions. For example, to satisfy the demand variation that is typical for the power and communication systems and reduce the cost, these systems usually adjust their operating regimes. The transition rate matrices under distinct operating regimes are assumed to be different and the sojourn times in distinct regimes are governed by a finite state Markov chain. By using the theory of Markov process, Ion channel theory, and Laplace transforms, the up time of the system are studied. A numerical example is given to illustrate the obtained results. The effect of sojourn times in distinct regimes on the availability and the up time are also discussed in the numerical example.展开更多
The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same ...The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same period, workflow management has experienced significant development, but has become more focused on the industry. However, it seems to us that document workflows have not had the same interest for the scientific community. But nowadays, the emergence and supremacy of the Internet in electronic exchanges are leading to a massive dematerialization of documents;which requires a conceptual reconsideration of the organizational framework for the processing of said documents in both public and private administrations. This problem seems open to us and deserves the interest of the scientific community. Indeed, EDM has mainly focused on the storage (referencing) and circulation of documents (traceability). It paid little attention to the overall behavior of the system in processing documents. The purpose of our researches is to model document processing systems. In the previous works, we proposed a general model and its specialization in the case of small documents (any document processed by a single person at a time during its processing life cycle), which represent 70% of documents processed by administrations, according to our study. In this contribution, we extend the model for processing small documents to the case where they are managed in a system comprising document classes organized in subclasses;which is the case for most administrations. We have thus observed that this model is a Markovian <i>M<sup>L×K</sup>/M<sup>L×K</sup>/</i>1 queues network. We have analyzed the constraints of this model and deduced certain characteristics and metrics. <span style="white-space:normal;"><i></i></span><i>In fine<span style="white-space:normal;"></span></i>, the ultimate objective of our work is to design a document workflow management system, integrating a component of global behavior prediction.展开更多
This paper proposes a novel model named as “imprecise stochastic process model” to handle the dynamic uncertainty with insufficient sample information in real-world problems. In the imprecise stochastic process mode...This paper proposes a novel model named as “imprecise stochastic process model” to handle the dynamic uncertainty with insufficient sample information in real-world problems. In the imprecise stochastic process model, the imprecise probabilistic model rather than a precise probability distribution function is employed to characterize the uncertainty at each time point for a time-variant parameter, which provides an effective tool for problems with limited experimental samples. The linear correlation between variables at different time points for imprecise stochastic processes is described by defining the auto-correlation coefficient function and the crosscorrelation coefficient function. For the convenience of analysis, this paper gives the definition of the P-box-based imprecise stochastic process and categorizes it into two classes: parameterized and non-parameterized P-box-based imprecise stochastic processes. Besides, a time-variant reliability analysis approach is developed based on the P-box-based imprecise stochastic process model,through which the interval of dynamic reliability for a structure under uncertain dynamic excitations or time-variant factors can be obtained. Finally, the effectiveness of the proposed method is verified by investigating three numerical examples.展开更多
Due to the randomness and time dependence of the factors affecting software reliability, most software reliability models are treated as stochastic processes, and the non-homogeneous Poisson process(NHPP) is the most ...Due to the randomness and time dependence of the factors affecting software reliability, most software reliability models are treated as stochastic processes, and the non-homogeneous Poisson process(NHPP) is the most used one.However, the failure behavior of software does not follow the NHPP in a statistically rigorous manner, and the pure random method might be not enough to describe the software failure behavior. To solve these problems, this paper proposes a new integrated approach that combines stochastic process and grey system theory to describe the failure behavior of software. A grey NHPP software reliability model is put forward in a discrete form, and a grey-based approach for estimating software reliability under the NHPP is proposed as a nonlinear multi-objective programming problem. Finally, four grey NHPP software reliability models are applied to four real datasets, the dynamic R-square and predictive relative error are calculated. Comparing with the original single NHPP software reliability model, it is found that the modeling using the integrated approach has a higher prediction accuracy of software reliability. Therefore, there is the characteristics of grey uncertain information in the NHPP software reliability models, and exploiting the latent grey uncertain information might lead to more accurate software reliability estimation.展开更多
In order to improve the influence of the uncertain and dynamic of node enterprise behavior on the performance of supply chain,the method based on stochastic process algebra for description,analysis,validation and eval...In order to improve the influence of the uncertain and dynamic of node enterprise behavior on the performance of supply chain,the method based on stochastic process algebra for description,analysis,validation and evaluation of supply chain business process model is proposed.Firstly,the description of the uncertainty of node enterprise behavior is given using the extended Unified Modeling Language sequence diagram,and mapping rule is defined from the extended Unified Modeling Language sequence diagram to stochastic process algebra.Secondly,on the basis of the acquired stochastic process algebra model,the supply chain business process model is verified with Mobility Workbench.Finally,according to the operational semantics of stochastic process algebra,the continuous-time Markov chain,isomorphic with stochastic process algebra model,is built; and the system performance evaluation of transient status and stable status is respectively conducted in accordance with Markov transfer relations and the current state of system,obtaining the predicted performance value and average performance index value for a specific period of time.The simulation experiments show that the proposed method can accurately describe the stochastic behaviors of supply chain system and interactions among nodes,effectively verify the validity of the model,and objectively and exactly evaluate design of the supply chain.展开更多
文摘Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.
基金the National Natural Science Foundation of China(No.61703391)。
文摘For some products,degradation mechanisms change during testing,and therefore,their degradation patterns vary at different points in time;these points are called change-points.Owing to the limitation of measurement costs,time intervals for degradation measurements are usually very long,and thus,the value of change-points cannot be determined.Conventionally,a certain degradation measurement is selected as the change-point in a two-phase degradation process.According to the tendency of the two-phase degradation process,the change-point is probably located in the interval between two neighboring degradation measurements,and it is a fuzzy variable.The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results.In this paper,based on the fuzzy theory,a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed.First,a two-phase Wiener degradation model is developed according to the membership function of the change-point.Second,the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach.Finally,the proposed methodology is verified via a case study.The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.
文摘A two-stage directed Semi-Markov repairable network system is presented in this paper to model the performance of many transmission systems, such as power or oil transmission network, water or gas supply network, etc. The availability of the system is discussed by using Markov renewal theory, Laplace transform and probability analysis methods. A numerical example is given to illustrate the results obtained in the paper.
文摘Let Q be the Q-matrix of an irreducible, positive recurrent Markov process on a countable state space. We show that, under a number of conditions, the stationary distributions of the n × n north-west corner augmentations of Q converge in total variation to the stationary distribution of the process. Two conditions guaranteeing such convergence include exponential ergodicity and stochastic monotonicity of the process. The same also holds for processes dominated by a stochastically monotone Markov process. In addition, we shall show that finite perturbations of stochastically monotone processes may be viewed as being dominated by a stochastically monotone process, thus extending the scope of these results to a larger class of processes. Consequently, the augmentation method provides an attractive, intuitive method for approximating the stationary distributions of a large class of Markov processes on countably infinite state spaces from a finite amount of known information.
文摘At first, the concept of bridge reliability is given, followed with its mathematic model. Then, based on the analysis about the mechanism of the damage and repair of bridges, and the state diversion of bridge network, the state diversion process is proved to be birth-and-death process. In the end, the state diversion balance equation of bridge network is built, and the evaluation model of wartime bridge reliability is got. The model is used in a certain example, and it is proved to be precise and credible.
基金funded by the National Natural Science Foundation of China(No.61503014)。
文摘Aviation and aerospace system are typical Phased-Mission Systems(PMSs)featured with varying configuration,phased load condition and cross phase failure correlation.The coupling effect of Functional Dependency(FDEP)and Physical Dependency(PDEP)has a unique influence on the failure behavior of PMS.In this article,the coupling effect is analyzed,and the degradation of components is modeled with the positive drift wiener process,in which the drift coefficient is related to environmental conditions and operation stress.Finally,failure behavior and system reliability are simulated.An avionics controller is studied as a case,with the degradation time distribution model and simulation algorithm,the coupling effect and dynamical system reliability can be achieved.Results show that this modeling method can describe the coupling effects of FDEP and PDEP and their influence on the failure behavior and reliability of the PMS system.
文摘Gearbox in offshore wind turbines is a component with the highest failure rates during operation. Analysis of gearbox repair policy that includes economic considerations is important for the effective operation of offshore wind farms. From their initial perfect working states, gearboxes degrade with time, which leads to decreased working efficiency. Thus, offshore wind turbine gearboxes can be considered to be multi-state systems with the various levels of productivity for different working states. To efficiently compute the time-dependent distribution of this multi-state system and analyze its reliability, application of the nonhomogeneous continuous-time Markov process(NHCTMP) is appropriate for this type of object. To determine the relationship between operation time and maintenance cost, many factors must be taken into account, including maintenance processes and vessel requirements. Finally, an optimal repair policy can be formulated based on this relationship.
文摘In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.
文摘In this article, we summarize some results on invariant non-homogeneous and dynamic-equilibrium (DE) continuous Markov stochastic processes. Moreover, we discuss a few examples and consider a new application of DE processes to elements of survival analysis. These elements concern the stochastic quadratic-hazard-rate model, for which our work 1) generalizes the reading of its It? stochastic ordinary differential equation (ISODE) for the hazard-rate-driving independent (HRDI) variables, 2) specifies key properties of the hazard-rate function, and in particular, reveals that the baseline value of the HRDI variables is the expectation of the DE solution of the ISODE, 3) suggests practical settings for obtaining multi-dimensional probability densities necessary for consistent and systematic reconstruction of missing data by Gibbs sampling and 4) further develops the corresponding line of modeling. The resulting advantages are emphasized in connection with the framework of clinical trials of chronic obstructive pulmonary disease (COPD) where we propose the use of an endpoint reflecting the narrowing of airways. This endpoint is based on a fairly compact geometric model that quantifies the course of the obstruction, shows how it is associated with the hazard rate, and clarifies why it is life-threatening. The work also suggests a few directions for future research.
基金supported by the National Natural Science Foundation of China(72001026).
文摘This paper proposes reliability and maintenance models for systems suffering random shocks arriving according to a non-homogeneous Poisson process.The system degradation process include two stages:from the installation of a new system to an initial point of a defect(normal stage),and then from that point to failure(defective stage),following the delay time concept.By employing the virtual age method,the impact of external shocks on the system degradation process is characterized by random virtual age increment in the two stages,resulting in the corresponding two-stage virtual age process.When operating in the defective state,the system becomes more susceptible to fatigue and suffers from a greater aging rate.Replacement is carried out either on failure or on the detection of a defective state at periodic or opportunistic inspections.This paper evaluates system reliability performance and investigates the optimal opportunistic maintenance policy.A case study on a cooling system is given to verify the obtained results.
文摘I. INTRODUCTION AND DEFINITIONS In this report, we shall give a simple counterexample to negative Theorem 1 and Proposition 3 (c)(ii)in [1] and explain the difference between the large-past Markov property and *-Markov property. Thereby some mistakes are cleared up.
文摘This paper contributes to the structural reliability problem by presenting a novel approach that enables for identification of stochastic oscillatory processes as a critical input for given mechanical models. Identification development follows a transparent image processing paradigm completely independent of state-of-the-art structural dynamics, aiming at delivering a simple and wide purpose method. Validation of the proposed importance sampling strategy is based on multi-scale clusters of realizations of digitally generated non-stationary stochastic processes. Good agreement with the reference pure Monte Carlo results indicates a significant potential in reducing the computational task of first passage probabilities estimation, an important feature in the field of e.g., probabilistic seismic design or risk assessment generally.
基金supported by the National Natural Science Foundation of China (71071020 60705036)Beijing Excellent Doctoral Dissertation Instructor Project of Humanities and Social Sciences(yb20091000701)
文摘Compared with the classical Markov repairable system, the Markov repairable system with stochastic regimes switching introduced in the paper provides a more realistic description of the practical system. The system can be used to model the dynamics of a repairable system whose performance regimes switch according to the external conditions. For example, to satisfy the demand variation that is typical for the power and communication systems and reduce the cost, these systems usually adjust their operating regimes. The transition rate matrices under distinct operating regimes are assumed to be different and the sojourn times in distinct regimes are governed by a finite state Markov chain. By using the theory of Markov process, Ion channel theory, and Laplace transforms, the up time of the system are studied. A numerical example is given to illustrate the obtained results. The effect of sojourn times in distinct regimes on the availability and the up time are also discussed in the numerical example.
文摘The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same period, workflow management has experienced significant development, but has become more focused on the industry. However, it seems to us that document workflows have not had the same interest for the scientific community. But nowadays, the emergence and supremacy of the Internet in electronic exchanges are leading to a massive dematerialization of documents;which requires a conceptual reconsideration of the organizational framework for the processing of said documents in both public and private administrations. This problem seems open to us and deserves the interest of the scientific community. Indeed, EDM has mainly focused on the storage (referencing) and circulation of documents (traceability). It paid little attention to the overall behavior of the system in processing documents. The purpose of our researches is to model document processing systems. In the previous works, we proposed a general model and its specialization in the case of small documents (any document processed by a single person at a time during its processing life cycle), which represent 70% of documents processed by administrations, according to our study. In this contribution, we extend the model for processing small documents to the case where they are managed in a system comprising document classes organized in subclasses;which is the case for most administrations. We have thus observed that this model is a Markovian <i>M<sup>L×K</sup>/M<sup>L×K</sup>/</i>1 queues network. We have analyzed the constraints of this model and deduced certain characteristics and metrics. <span style="white-space:normal;"><i></i></span><i>In fine<span style="white-space:normal;"></span></i>, the ultimate objective of our work is to design a document workflow management system, integrating a component of global behavior prediction.
基金supported by the Science Challenge Project,China(No.TZ2018007)the National Science Fund for Distinguished Young Scholars,China(No.51725502)+2 种基金the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.51621004)the Fundamental Research Foundation of China(No.JCKY2020110C105)the National Natural Science Foundation of China(No.52105253)。
文摘This paper proposes a novel model named as “imprecise stochastic process model” to handle the dynamic uncertainty with insufficient sample information in real-world problems. In the imprecise stochastic process model, the imprecise probabilistic model rather than a precise probability distribution function is employed to characterize the uncertainty at each time point for a time-variant parameter, which provides an effective tool for problems with limited experimental samples. The linear correlation between variables at different time points for imprecise stochastic processes is described by defining the auto-correlation coefficient function and the crosscorrelation coefficient function. For the convenience of analysis, this paper gives the definition of the P-box-based imprecise stochastic process and categorizes it into two classes: parameterized and non-parameterized P-box-based imprecise stochastic processes. Besides, a time-variant reliability analysis approach is developed based on the P-box-based imprecise stochastic process model,through which the interval of dynamic reliability for a structure under uncertain dynamic excitations or time-variant factors can be obtained. Finally, the effectiveness of the proposed method is verified by investigating three numerical examples.
基金supported by the National Natural Science Foundation of China (71671090)the Fundamental Research Funds for the Central Universities (NP2020022)the Qinglan Project of Excellent Youth or Middle-Aged Academic Leaders in Jiangsu Province。
文摘Due to the randomness and time dependence of the factors affecting software reliability, most software reliability models are treated as stochastic processes, and the non-homogeneous Poisson process(NHPP) is the most used one.However, the failure behavior of software does not follow the NHPP in a statistically rigorous manner, and the pure random method might be not enough to describe the software failure behavior. To solve these problems, this paper proposes a new integrated approach that combines stochastic process and grey system theory to describe the failure behavior of software. A grey NHPP software reliability model is put forward in a discrete form, and a grey-based approach for estimating software reliability under the NHPP is proposed as a nonlinear multi-objective programming problem. Finally, four grey NHPP software reliability models are applied to four real datasets, the dynamic R-square and predictive relative error are calculated. Comparing with the original single NHPP software reliability model, it is found that the modeling using the integrated approach has a higher prediction accuracy of software reliability. Therefore, there is the characteristics of grey uncertain information in the NHPP software reliability models, and exploiting the latent grey uncertain information might lead to more accurate software reliability estimation.
基金Sponsored by the National High-Tech.R&D Program for CIMS,China(Grant No.2007AA04Z146)
文摘In order to improve the influence of the uncertain and dynamic of node enterprise behavior on the performance of supply chain,the method based on stochastic process algebra for description,analysis,validation and evaluation of supply chain business process model is proposed.Firstly,the description of the uncertainty of node enterprise behavior is given using the extended Unified Modeling Language sequence diagram,and mapping rule is defined from the extended Unified Modeling Language sequence diagram to stochastic process algebra.Secondly,on the basis of the acquired stochastic process algebra model,the supply chain business process model is verified with Mobility Workbench.Finally,according to the operational semantics of stochastic process algebra,the continuous-time Markov chain,isomorphic with stochastic process algebra model,is built; and the system performance evaluation of transient status and stable status is respectively conducted in accordance with Markov transfer relations and the current state of system,obtaining the predicted performance value and average performance index value for a specific period of time.The simulation experiments show that the proposed method can accurately describe the stochastic behaviors of supply chain system and interactions among nodes,effectively verify the validity of the model,and objectively and exactly evaluate design of the supply chain.
