Mathematical Models and Applicable Technologies to Forecast, Analyze, and Optimize Quality and Risks for Complex Systems

ICTIS 2011 ◽  
2011 ◽  
Author(s):  
Andrey Kostogryzov ◽  
Vladimir Krylov ◽  
Andrey Nistratov ◽  
George Nistratov ◽  
Vladimir Popov ◽  
...  
Keyword(s):  
Complex Systems ◽  
Mathematical Models

Design and Analysis of Computer Experiments

2017 ◽  
pp. 264-279
Author(s):  
Xinwei Deng ◽  
Ying Hung ◽  
C. Devon Lin
Keyword(s):  
Complex Systems ◽  
Mathematical Models ◽  
Gaussian Process ◽  
Computer Simulations ◽  
Process Modeling ◽  
Computer Experiments ◽  
Space Filling ◽  
Science And Engineering ◽  
The Past ◽  
Statistical Approaches

Computer experiments refer to the study of complex systems using mathematical models and computer simulations. The use of computer experiments becomes popular for studying complex systems in science and engineering. The design and analysis of computer experiments have received broad attention in the past decades. In this chapter, we present several widely used statistical approaches for design and analysis of computer experiments, including space-filling designs and Gaussian process modeling. A special emphasis is given to recently developed design and modeling techniques for computer experiments with quantitative and qualitative factors.

scholarly journals Minkowski’s Inequality Based Sensitivity Analysis of Fuzzy Signatures

2016 ◽  
Vol 6 (4) ◽  
pp. 219-229 ◽  
Author(s):  
István Á. Harmati ◽  
Ádám Bukovics ◽  
László T. Kóczy
Keyword(s):  
Sensitivity Analysis ◽  
Complex Systems ◽  
Mathematical Models ◽  
Human Activities ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Final Conclusion ◽  
Minkowski’S Inequality ◽  
Precise Data ◽  
Input Parameters

Abstract Fuzzy signatures were introduced as special tools to describe and handle complex systems without their detailed mathematical models. The input parameters of these systems naturally have uncertainties, due to human activities or lack of precise data. These uncertainties influence the final conclusion or decision about the system. In this paper we discuss the sensitivity of the weigthed general mean aggregation operator to the uncertainty of the input values, then we analyse the sensitivity of fuzzy signatures equipped with these aggregation operators. Finally, we apply our results to a fuzzy signature used in civil enginnering.

Degradation Assessment in Complex Systems

2006 ◽  
Author(s):  
Vaidas Matuzas ◽  
Juozas Augutis ◽  
Eugenijus Uspuras
Keyword(s):  
Mathematical Model ◽  
Complex Systems ◽  
Mathematical Models ◽  
Mathematical Description ◽  
Nuclear Power ◽  
Power Plants ◽  
Reliability Assessment ◽  
Main Process ◽  
Main Attention ◽  
Network Systems

Components condition could change dynamically because of various dependencies existing in complex systems since usually not only physical connections exist in the system. Various processes (as degradation or wear out, reliability decrease, failures) affecting one component have influence to condition of other components as well. Current paper is devoted to the analysis and development of mathematical models to the reliability assessment of network systems. Degradation as the main process in the network systems is taken into account. The main attention in present work was paid to the mathematical description of the degradation spreading mechanism in network systems. Developed recursive mathematical model allows assess degradation in network systems during various time moments. Developed methods can be applied for assessment of various risk estimates of hazardous systems such as systems at nuclear power plants.

10.2.2 Mathematical Models of Emergence in Complex Systems-of-systems

2013 ◽  
Vol 23 (1) ◽  
pp. 889-903 ◽  
Author(s):  
W. Clifton Baldwin ◽  
Stephanie Hostetler ◽  
Wilson N. Felder
Keyword(s):  
Complex Systems ◽  
Mathematical Models ◽  
Systems Of Systems

scholarly journals Chebanov law and Vakar formula in mathematical models of complex systems

2015 ◽  
Vol 21 ◽  
pp. 27-33 ◽  
Author(s):  
Josué-Antonio Nescolarde-Selva ◽  
Josep-Lluis Usó-Doménech ◽  
Miguel Lloret-Climent ◽  
Lucía González-Franco
Keyword(s):  
Complex Systems ◽  
Mathematical Models

scholarly journals Anti-Swing Fuzzy Controller Applied in a 3D Crane System

2012 ◽  
Vol 2 (2) ◽  
pp. 196-200 ◽  
Author(s):  
D. Antic ◽  
Z. Jovanovic ◽  
S. Peric ◽  
S. Nikolic ◽  
M. Milojkovic ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Complex Systems ◽  
Mathematical Models ◽  
Fuzzy Controller ◽  
Main Difficulty ◽  
Trial And Error ◽  
Nonlinear Mathematical Models ◽  
Highly Nonlinear ◽  
Experimental Laboratory ◽  
Input Variables

It is well known that fuzzy logic can be used in the control of complex systems described by highly nonlinear mathematical models. However, the main difficulty in the design of a fuzzy controller comes with the adjustment of the controller’s parameters that are usually determined by human experts’ knowledge or trial and error methods. In this paper, we describe an implementation of fuzzy logic in order to reduce oscillations during the positioning of a 3D crane system. The fuzzy controller’s structure is quite simple, requiring only two input variables. The proposed fuzzy controller has been applied to an experimental laboratory framework and results show that oscillations are significantly reduced.

FORECASTING THE PERFORMANCE OF THE TRANSPORT SYSTEM

2020 ◽  
Vol 4 (26) ◽  
pp. 72-79
Author(s):  
Y. Y. Eglit ◽  
◽  
К. Y. Eglit ◽  
M. A. Shapovalova ◽  
D. G. Semina ◽  
...  
Keyword(s):  
Complex Systems ◽  
Mathematical Models ◽  
Key Words ◽  
Transport System ◽  
Key Words Transport

The article is devoted to the development of a methodology for predicting the performance of the transport system using mathematical models that can be used to effectively analyze and predict the functioning of complex systems. Key words: transport system, fleet, ships, analysis, forecasting, mathematical models.

On some new types of mathematical models of complex systems

2006 ◽  
pp. 10-26 ◽  
Author(s):  
Ye. A. Asarin ◽  
V. S. Kozyakin ◽  
M. A. Krasnosel'skii ◽  
N. A. Kuznetsov ◽  
A. V. Pokrovskii
Keyword(s):  
Complex Systems ◽  
Mathematical Models
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