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True state-space complexity prediction: By the proxel-based simulation method
2009
2009 International Conference on Innovations in Information Technology (IIT)
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Its early diagnosis is especially significant in the case of proxel-based simulation, as it can lead towards hybridization of the method by employing discrete phase approximations for the critical states ...
All state-space based simulation methods are doomed by the phenomenon of state-space explosion. ...
We claim that the discrete state space (which is equivalent to a reachability graph in Petri net terminology) is not a single factor that determines the complexity of models" proxel-based simulation. ...
doi:10.1109/iit.2009.5413761
fatcat:cmrgmcejozc5dkf4v4kreilbpq
Hidden non-Markovian reward Models : Virtual stochastic sensors for hybrid systems
2012
Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC)
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We are interested in partially observable hybrid systems whose discrete behavior is stochastic and unobservable, and for which samples of some of the continuous variables are available. ...
Based on these samples of the continuous variables, we show how the hidden discrete behavior may be reconstructed computationally, which was previously not possible. ...
Stochastic Reward Nets (SRN) (Muppala, Ciardo, and Trivedi 1994) use a stochastic Petri net as description of the dynamic process of the system. ...
doi:10.1109/wsc.2012.6465052
dblp:conf/wsc/KrullH12
fatcat:ufjahyx3xzb47l6wy5dndxumla
Proxel-Based Performability Analysis of Non-Markovian Phased-Mission Systems
2010
2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation
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Lower level components of systems can be described using any formalism, i.e. Petri nets or state-transition diagrams. ...
The proxel-based method allows for a general class of phased-mission systems to be analyzed without imposing the typical limitations on the models or sacrificing accuracy. ...
Recently, there has been a Petri net-based approach that handles general non-exponentially distributed activities [20] . ...
doi:10.1109/ams.2010.118
fatcat:h2bti5pdkbc7nfupagoelnllfe
Reconstructing Model Parameters in Partially-Observable Discrete Stochastic Systems
[chapter]
2011
Lecture Notes in Computer Science
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Here, the source of each defective item can be reconstructed later based solely on the time-stamped test protocol. ...
The analysis of partially-observable discrete stochastic systems reconstructs the unobserved behavior of real-world systems. ...
a non-Markovian stochastic Petri net [1, 3] . ...
doi:10.1007/978-3-642-21713-5_12
fatcat:muoyq66skvc6zblh7gfehxuyvu
Using hidden non-Markovian Models to reconstruct system behavior in partially-observable systems
2012
Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
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The combination of Hidden non-Markovian Models and Proxel-based simulation holds the potential to reconstruct unobserved information from partial or even noisy output protocols of a system. ...
The approach uses Hidden non-Markovian Models to model the partiallyobservable system and Proxel-based simulation to analyze the recorded system output. ...
Here we are using a kind of non-Markovian stochastic Petri net (SPN), which contains elements of some of the most common extensions to the original Petri net paradigm [1] . ...
doi:10.4108/icst.simutools2010.8641
dblp:conf/simutools/BuchholzKSH10
fatcat:5bh4odcza5aerfgmt3xjwt47b4
Virtual Stochastic Sensors for Reconstructing Job Shop Production Workflows
2013
2013 8th EUROSIM Congress on Modelling and Simulation
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Keywords-discrete stochastic systems; hidden non-markovian models; virtual stochastic sensors; behavior reconstruction; workflow modelling and simulation; analytical simulation I. 2013 8th EUROSIM Congress ...
In order to deal with probabilistic decisions in the workflows, we extended Hidden non-Markovian Models to include immediate transitions and modified the corresponding Proxel-based behavior reconstruction ...
We used augmented stochastic Petri nets (ASPN) [1] as higher level description of the HnMM to represent the job shop workflows. ...
doi:10.1109/eurosim.2013.57
fatcat:4cxwbvd2dnbdldnh7gjlesa42e
Improving the Efficiency of the Proxel Method by Using Individual Time Steps
[chapter]
2009
Lecture Notes in Computer Science
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Proxel-based simulation can outperform discrete event-based approaches in the analysis of small stiff DSM, which can occur for example in reliability modeling. ...
This increases the applicability of Proxels, by enabling the analysis of larger and therefore more realistic models. ...
It shows a small stochastic Petri net with two consecutive transitions that differ in speed by a factor of 10. Both have a normal distribution and the same coefficient of variation. ...
doi:10.1007/978-3-642-02205-0_9
fatcat:53t2pp34xfeyhjjrseaoitclhy
A Hybrid Multi-trajectory Simulation Algorithm for the Performance Evaluation of Stochastic Petri Nets
[chapter]
2017
Lecture Notes in Computer Science
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The paper proposes a hybrid performance evaluation algorithm for Stochastic Petri Nets that integrates elements of both methods. ...
Standard performance evaluation methods for discrete-state stochastic models such as Petri nets either generate the reachability graph followed by a numerical solution of equations, or use some variant ...
Performance Evaluation of Stochastic Petri Nets Stochastic Petri nets can be defined as SPN = (P, T , Pre, Post, λ, m 0 , RV ). ...
doi:10.1007/978-3-319-66335-7_7
fatcat:nspiolhnknh5vcox2jr4bvhwsa
The proxel-based method - formalisation, analysis and applications
[article]
2018
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The proxel-based method is an intuitive approach to analysing discrete stochastic models, such as are described by stochastic Petri nets or queuing systems for example. ...
Further, the thesis examines some of the application areas of the proxel-based method. 157 ix PDE Partial differential equation PDF Probability density function SPN Stochastic Petri net xix ...
The proxel-based method is, however, not limited to models described by means of stochastic Petri nets. ...
doi:10.25673/4648
fatcat:vcy2mowbfnh5lhd43ni4yownmi
Approximation of Discrete Phase-Type Distributions
38th Annual Simulation Symposium
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The analysis of discrete stochastic models such as generally distributed stochastic Petri nets can be done using state space-based methods. ...
Discrete phases also fit in well with current research on proxel-based simulation. They can represent infinite support distribution functions with considerably fewer Markov chain states than proxels. ...
A goal of our future research is to combine proxels and DPH to form a general state space-based simulation method. ...
doi:10.1109/anss.2005.12
dblp:conf/anss/IsenseeH05
fatcat:wpqoru27ire5lfdtzvrfafd53i
A New Approach for Computing Conditional Probabilities of General Stochastic Processes
39th Annual Simulation Symposium (ANSS'06)
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The goal is to develop an algorithm that adapts known Hidden Markov Model algorithms for use with proxel-based simulation. ...
In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. ...
Proxel-based simulation was introduced by Horton in 2002 [5] as a state space-based analysis method for general continuous-time stochastic models. ...
doi:10.1109/anss.2006.7
dblp:conf/anss/WickbornISLH06
fatcat:4fes5t5i5fdqlbzt55w75ftqo4
Virtual Stochastic Sensors: How to Gain Insight into Partially Observable Discrete Stochastic Systems
2011
Artificial Intelligence and Applications / 718: Modelling, Identification, and Control
unpublished
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KEY WORDS virtual stochastic sensor, discrete stochastic model, state space-based simulation, time series analysis ...
This paper introduces the idea of a Virtual Stochastic Sensor. This paradigm enables the analysis of unobservable processes in discrete stochastic systems. ...
Using Proxel-based simulation to compute the value of the Virtual Stochastic Sensor imposes another restriction on the system to be analyzed. ...
doi:10.2316/p.2011.718-041
fatcat:zdadtgh32fc5xjox7stqzqgd7y
Conversive Hidden non-Markovian models
[article]
2018
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Furthermore, augmented stochastic Petri nets (ASPNs) were introduced as a conceptual model for our class of systems and the Proxel method was shown to be able to simulate possible behavior of the class ...
Stochastic Petri nets [55] are a class of conceptual models that can visualize various different kinds of discrete systems [5, 50] . ...
Thus, in each time step the Proxel probabilities are multiplied by such a polynomial, increasing the degree of the Proxel probability polynomial by at least one. ...
doi:10.25673/5535
fatcat:5w3gdjaddvfd3mrciarylo3zki