Prediction in dynamic system a divide and conquer approach

2005 ◽  
Author(s):  
G. Chakraborty ◽  
H. Watanabe ◽  
B. Chakraborty
Keyword(s):  
Dynamic System ◽  
Divide And Conquer ◽  
System A

Leontev Input-Output Balance Model as a Dynamic System Control Problem

2021 ◽  
pp. 66-82
Author(s):  
S.N. Masaev
Keyword(s):  
Dynamic System ◽  
Matrix Representation ◽  
External Environment ◽  
Balance Model ◽  
System Control ◽  
Operational Mode ◽  
Input Output ◽  
System A ◽  
The Matrix ◽  
Research Show

The purpose of the study was to determine the problem of control of a dynamic system of higher dimension. Relying on Leontev input-output balance, we formalized the dynamic system and synthesized its control. Within the research, we developed a mathematical model that combines different working objects that consume and release various resources. The value of the penalty for all nodes and objects is introduced into the matrix representation of the problem, taking into account various options for their interaction, i.e., the observation problem. A matrix representation of the planning task at each working object is formed. For the formed system, a control loop is created; the influencing parameters of the external environment are indicated. We calculated the system operational mode, taking into account the interaction of the nodes of objects with each other when the parameters of the external environment influence them. Findings of research show that in achieving a complex result, the system is inefficient without optimal planning and accounting for the matrix of penalties for the interaction of nodes and objects of the dynamic system with each other. In a specific example, for a dynamic system with a dimension of 4.8 million parameters, we estimated the control taking into account the penalty matrix, which made it possible to increase the inflow of additional resources from the outside by 2.4 times from 130 billion conv. units up to 310 conv. units in 5 years. Taking into account the maximum optimization of control in the nodes, an increase of 3.66 times in the inflow of additional resources was ensured --- from 200.46 to 726.62 billion rubles

Fluctuation complexity of agent-based financial time series model by stochastic Potts system

2015 ◽  
Vol 26 (11) ◽  
pp. 1550123 ◽  
Author(s):  
Weijia Hong ◽  
Jun Wang
Keyword(s):  
Time Series ◽  
Dynamic System ◽  
Financial Time Series ◽  
Composite Index ◽  
Time Series Model ◽  
Agent Based ◽  
Financial Time ◽  
System A ◽  
Challenging Tasks ◽  
Financial Research

Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.

scholarly journals Self-Powered Dynamic Systems in the Framework of Optimal Uncertainty Quantification

2017 ◽  
Vol 139 (9) ◽  
Author(s):  
Farbod Khoshnoud ◽  
Ibrahim I. Esat ◽  
Clarence W. de Silva ◽  
Michael M. McKerns ◽  
Houman Owhadi
Keyword(s):  
Renewable Energy ◽  
Dynamic System ◽  
Uncertainty Quantification ◽  
Supply And Demand ◽  
System A ◽  
Rigorous Framework ◽  
Energy Excess ◽  
Optimal Bounds ◽  
Self Powered ◽  
Solar Powered

The energy that is needed for operating a self-powered device is provided by the energy excess in the system in the form of kinetic energy, or a combination of regenerative and renewable energy. This paper addresses the energy exchange issues pertaining to regenerative and renewable energy in the development of a self-powered dynamic system. A rigorous framework that explores the supply and demand of energy for self-powered systems is developed, which considers uncertainties and optimal bounds, in the context of optimal uncertainty quantification. Examples of regenerative and solar-powered systems are given, and the analysis of self-powered feedback control for developing a fully self-powered dynamic system is discussed.

On Integrating an Integrative: Implications for Implementing a Biofeedback Program into an Inpatient Rehabilitation Hospital

Biofeedback ◽  
2014 ◽  
Vol 42 (3) ◽  
pp. 115-120
Author(s):  
Antoinette Giedzinska-Simons
Keyword(s):  
Mental Health ◽  
Dynamic System ◽  
Health System ◽  
Mental Health System ◽  
Inpatient Rehabilitation ◽  
Rehabilitation Program ◽  
Rehabilitation Hospital ◽  
System A

Implementing a viable biofeedback program into an integrative mental health inpatient rehabilitation program has its appeals and its challenges. This article describes the biofeedback program within the Sierra Tucson inpatient rehabilitation hospital. The fact that the field of biofeedback provides a dynamic system of training, education, and empowerment can yield creative programmatic solutions toward integrating this therapy to coalesce within a greater integrative mental health system. A brief outline of the challenges to consider when implementing such a program is offered, along with further discussion regarding the Sierra Tucson program's model and methods.

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