: We propose a general procedure to be applied for the estimation of the First and Total order Differential Importance Measures when the evaluation of the reliability / availability performances of the system requires the application of MonteCarlo techniques. By means of the application of Importance sampling techniques, all the output variables (system Unavailability for different values of the input variables) are computed contemporaneously, on the basis of the same sequence of the involved components, events type (failure / repair) and transition times for each trial. The failure/repair probabilities are forced to be the same for all components; the transition times are sampled from the unbiased probability distributions or by forcing th...
none3The paper presents a general approach to assess the performance of a networked system, made up ...
The paper refers to the evaluation of the Unavailability of systems made by repairable binary compon...
Piecewise deterministic Markov processes (PDMPs) can be used to model complex dynamical industrial s...
: We propose a general procedure to be applied for the estimation of the First and Total order Diffe...
Very complex systems occur nowadays quite frequently in many technological areas and they are often ...
This paper focuses on the reliability analysis of multicomponent systems by the importance sampling ...
This paper presents the development of the differential importance measures (DIM), proposed recently...
International audienceThis paper describes how importance sampling can be applied to efficiently est...
Situations in which historical data is not available are simulated using availability estimation and...
In the present paper we use discrete event simulation in order to analyze a binary monotone system o...
The reliability of a complex industrial system can rarely be assessed analytically. As system failur...
We are interested in estimating, through simulation, the probability of entering a rare failure stat...
A new approach to evaluate the reliability of structural systems using a Monte Carlo variance reduct...
This paper targets the simulation of continuous-time Markov chain models of fault-tolerant systems w...
This paper targets the simulation of continuous-time Markov chain models of fault-tolerant systems w...
none3The paper presents a general approach to assess the performance of a networked system, made up ...
The paper refers to the evaluation of the Unavailability of systems made by repairable binary compon...
Piecewise deterministic Markov processes (PDMPs) can be used to model complex dynamical industrial s...
: We propose a general procedure to be applied for the estimation of the First and Total order Diffe...
Very complex systems occur nowadays quite frequently in many technological areas and they are often ...
This paper focuses on the reliability analysis of multicomponent systems by the importance sampling ...
This paper presents the development of the differential importance measures (DIM), proposed recently...
International audienceThis paper describes how importance sampling can be applied to efficiently est...
Situations in which historical data is not available are simulated using availability estimation and...
In the present paper we use discrete event simulation in order to analyze a binary monotone system o...
The reliability of a complex industrial system can rarely be assessed analytically. As system failur...
We are interested in estimating, through simulation, the probability of entering a rare failure stat...
A new approach to evaluate the reliability of structural systems using a Monte Carlo variance reduct...
This paper targets the simulation of continuous-time Markov chain models of fault-tolerant systems w...
This paper targets the simulation of continuous-time Markov chain models of fault-tolerant systems w...
none3The paper presents a general approach to assess the performance of a networked system, made up ...
The paper refers to the evaluation of the Unavailability of systems made by repairable binary compon...
Piecewise deterministic Markov processes (PDMPs) can be used to model complex dynamical industrial s...