Sökning: "Semi-Markov processes"
Visar resultat 1 - 5 av 7 uppsatser innehållade orden Semi-Markov processes.
1. Reliability Based Classification of Transitions in Complex Semi-Markov Models
Master-uppsats, KTH/Matematisk statistikSammanfattning : Markov processes have a long history of being used to model safety critical systems. However, with the development of autonomous vehicles and their increased complexity, Markov processes have been shown to not be sufficiently precise for reliability calculations. LÄS MER
2. Modelling Parallel Stochastic-Time Systems Using Timed and Synchronous Layers : Introducing the Parallel Stochastic Timed State Machine
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In the development phase of real-world cyper-physical systems, modelling and analysis often plays a vital role. For instance, before a new system is produced and deployed, questions such as ‘what is the probability that the system will fail within its lifetime?’ must be answered. LÄS MER
3. Approximation of General Semi-Markov Models Using Expolynomials
Master-uppsats, KTH/Matematisk statistikSammanfattning : Safety analysis is critical when developing new engineering systems. Many systems have to function under randomly occurring events, making stochastic processes useful in a safety modelling context. However, a general stochastic process is very challenging to analyse mathematically. LÄS MER
4. Modelling Safety of Autonomous Driving with Semi-Markov Processes
Kandidat-uppsats,Sammanfattning : With the advent of autonomous vehicles, the issue of safety-evaluationhas become key. ISO26262 recommends using Markov chains. However, in their most common form, Markov chains lack the flexibility required to model non- exponential probability distributions and systems displaying parallelism. LÄS MER
5. Quantified safety modeling of autonomous systems with hierarchical semi-Markov processes
Master-uppsats, KTH/Optimeringslära och systemteoriSammanfattning : In quantified safety engineering, mathematical probability models are used to predict the risk of failure or hazardous events in systems. Markov processes have commonly been utilized to analyze the safety of systems modeled as discrete-state stochastic processes. LÄS MER