scholarly journals Research of a multithreaded non-deterministic system model

2021 ◽  
Vol 34 (01) ◽  
pp. 193-204
Author(s):  
Dmitry V. Pashchenko ◽  
Dmitry A. Trokoz ◽  
Alexey I. Martyshkin ◽  
Tatyana Yu. Pashchenko ◽  
Mikhail M. Butaev ◽  
...  
Keyword(s):  
Positive Impact ◽  
Discrete Event ◽  
Finite State Automaton ◽  
Deterministic System ◽  
Professional Activities ◽  
Deterministic Systems ◽  
Parallel Data ◽  
Finite State ◽  
Event Model ◽  
Discrete Event Model

Managing the systems which behaviour is non-deterministic is one of the most important problems in modern management theory. Today, systems with structural and behavioural complexity are prevalent in all areas of human activity, and therefore, their research is of the utmost importance. Such systems, as opposed to deterministic systems, are called non-deterministic. They are characterised by difficult predictable behaviour determined both by external random influences, and within the systems themselves. A clear example of a non-deterministic system is crowds of people, factories, and computer networks and systems. The problem of non-deterministic behaviour directly within the context of professional activities can be seen using an example of building syntactic analysers. The aim of the paper is to design a class of systems oriented towards supporting elements of a discrete event model. The target of research is to simulate discrete event models. The subject of research is a creation of a discrete event model based on the behaviour of an undetermined finite state automaton. During the preparation of the paper, there was developed and practically implemented an algorithm for the application, which materializes the principle of working with threads. The results obtained in the paper are aimed at solving the problem of parallel data processing based on the parallelism of NFA's (non-deterministic finite automaton) behaviour when reading the input string characters. As a result, this should have a positive impact on the regulation of the simulation processes of a non-deterministic system, increasing its efficiency and stability. In conclusion, the algorithm of the application work is disclosed and conclusions about the effectiveness and efficiency of its development are drawn.

scholarly journals A discrete event model of clinical trial enrollment at eli lilly and company

2007 ◽  
Author(s):  
Bernard M. McGarvey ◽  
Nancy J. Dynes ◽  
Burch C. Lin ◽  
Wesley H. Anderson ◽  
James P. Kremidas ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Discrete Event ◽  
Event Model ◽  
Clinical Trial Enrollment ◽  
Discrete Event Model

Arena-Based Modeling of the Maintenance Operation for a Wind Farm

2013 ◽  
Vol 401-403 ◽  
pp. 2205-2208 ◽  
Author(s):  
Huai Zhong Li ◽  
Tong Jing ◽  
Hong Zhang
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Discrete Event ◽  
Onshore Wind ◽  
Electric System ◽  
System A ◽  
Factors Influencing ◽  
Event Model ◽  
Main Factors ◽  
Discrete Event Model

Wind energy has become a leading developing direction in electric power. The high cost associated with turbine maintenance is a key challenging issue in wind farm operation as wind turbines are hard-to access for inspection and repair. Analysis of an onshore wind farm is carried out in this paper in terms of the operation, failure, and maintenance. Failures are categorized into three classes according to the downtime. It is found that the pitch, gearbox and generator have the most amount of downtime, while the most number of failures is from the pitch and electric system. A discrete-event model is developed by using Arena to simulate the operation, failure occurrence, and maintenance of the wind turbines, with an aim to determine the main factors influencing maintenance costs and the availability of the turbines in the wind farm.

scholarly journals Validation of a Stochastic Discrete Event Model Predicting Virus Concentration on Nurse Hands

Risk Analysis ◽  
2019 ◽  
Vol 39 (8) ◽  
pp. 1812-1824 ◽  
Author(s):  
Amanda M. Wilson ◽  
Kelly A. Reynolds ◽  
Marc P. Verhougstraete ◽  
Robert A. Canales
Keyword(s):  
Discrete Event ◽  
Virus Concentration ◽  
Event Model ◽  
Discrete Event Model

scholarly journals Approaches to Modeling the Gas-Turbine Maintenance Process

2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Tai-Tuck Yu ◽  
James P. Scanlan ◽  
Richard M. Crowder ◽  
Gary B. Wills
Keyword(s):  
Decision Making ◽  
Gas Turbine ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Modeling ◽  
Human Decision ◽  
Event Model ◽  
Discrete Event Model

Discrete-event modeling has long been used for logistics and scheduling problems, while multi-agent modeling closely matches human decision-making process. In this paper, a metric-based comparison between the traditional discrete-event and the emerging agent-based modeling approaches is reported. The case study involved the implementation of two functionally identical models based on a realistic, nontrivial, civil aircraft gas turbine global repair operation. The size, structural complexity, and coupling metrics from the two models were used to gauge the benefits and drawbacks of each modeling paradigm. The agent-based model was significantly better than the discrete-event model in terms of execution times, scalability, understandability, modifiability, and structural flexibility. In contrast, and importantly in an engineering context, the discrete-event model guaranteed predictable and repeatable results and was comparatively easy to test because of its single-threaded operation. However, neither modeling approach on its own possesses all these characteristics nor can each handle the wide range of resolutions and scales frequently encountered in problems exemplified by the case study scenario. It is recognized that agent-based modeling can emulate high-level human decision-making and communication closely while discrete-event modeling provides a good fit for low-level sequential processes such as those found in manufacturing and logistics.

scholarly journals AGN variability time scales and the discrete-event model

2005 ◽  
Vol 443 (2) ◽  
pp. 451-463 ◽  
Author(s):  
P. Favre ◽  
T. J.-L. Courvoisier ◽  
S. Paltani
Keyword(s):  
Time Scales ◽  
Discrete Event ◽  
Event Model ◽  
Discrete Event Model
Sign in / Sign up

Export Citation Format

Share Document