• Title/Summary/Keyword: chaos analysis

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A Review on Two-Phase Flow Analysis using Chaos Theory (카오스 이론을 이용한 2상 유동 해석)

  • Kwon, Jeong-Tae;Kwon, Young-Chul;Kim, Kyoung-Min
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.56 no.1
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    • pp.23-27
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    • 2007
  • This article presents a review on chaos analysis of two-phase flow. Chaos theory has recently been applied to two-phase flow analysis, and it gives promising measures to quantitatively identify two-phase flow patterns and pool boiling behaviors. But, consistency of the calculated chaotic measures were not completely confirmed yet. More experimental data are requested for chaos analysis of two-phase flow. Also, chaos analysis methodology should be developed by experimental verification.

Nonlinear Time Series Analysis of Biological Chaos (생체 카오스의 비선형 시계열 데이터 분석)

  • 이병채;이명호
    • Journal of Biomedical Engineering Research
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    • v.15 no.3
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    • pp.347-354
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    • 1994
  • This paper describes a diagnostic protocol of nonlinear dynamic characteristics of biological system using chaos theory. An integrated chaos analysis system for the diagnosis of biological system was designed. We suggest a procedure of attractor reconstruction for reliable qualitative and quantitative analysis. The effect of autonomic nervous system activity on heart rate variability with power spectral analysis and its characteristics of chaotic attractors are investigated. The results show the applicability to evaluate the mental and physical conditions using nonlinear characteristics of biological signal.

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Chaos analysis of real estate auction sale price rate time series (부동산 경매 낙찰가율 시계열의 Chaos 분석)

  • Kang, Jun;Kim, Jiwoo;Lee, Hyun Jun;Oh, Kyong Joo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.371-381
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    • 2017
  • There has never been research on Chaos analysis using real estate auction sale price rate in Korea. In this study, three Chaos analysis methodologies - Hurst exponent, correlation dimension, and maximum Lyapunov exponent - in order to capture the nonlinear deterministic dynamic system characteristics. High level of Hurst exponent and the extremely low maximum Lyapunov exponent provide the tendency and the persistence of the data. The empirical results give two meaningful facts. First, monthly time lags of the correlation dimension are coincident with the time period from the approval auction start day to the sale price fixing day. Second, its weekly time lags correspond to the time period from the last day of request for sale price allocation to the sale price fixing day. Then, this study potentially examines the predictability of the real estate auction price rate time series.

New Chaos Map for BER Performance Improvement in Chaos Communication System Using CDSK (상관지연편이변조 방식의 혼돈(Chaos) 통신 방식에서 비트오류율 성능 향상을 위한 새로운 혼돈 지도)

  • Lee, Jun-Hyun;Ryu, Heung-Gyoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.8
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    • pp.629-637
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    • 2013
  • Chaos communication systems have the characteristics such as non-periodic, wide-band, non-predictability of signals and easy implementation. There have been many studies about chaos communication systems because of these advantages. But, chaos communication systems have low BER(Bit Error Rate) compare to general digital communication system. Existing researches on chaos communication systems only analyze BER performance according to various chaos maps. There are no studies on analysis of BER performance according to PDF(Probability Density Function) of chaos maps. In this paper, we analyze the BER performance according to changing parameter, equation, and initial values of chaos map's PDF. In addition, we propose new chaos map to improve BER performance. Simulation results show that BER performance of CDSK(Correlation Delay Shift Keying) is changed when PDF of chaos map changed. And the proposed chaos map has a better BER performance compare to previous chaos maps such as Tent map, Logistic map, and Henon map.

A polynomial chaos method to the analysis of the dynamic behavior of spur gear system

  • Guerine, A.;El Hami, A.;Fakhfakh, T.;Haddar, M.
    • Structural Engineering and Mechanics
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    • v.53 no.4
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    • pp.819-831
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    • 2015
  • In this paper, we propose a new method for taking into account uncertainties based on the projection on polynomial chaos. The new approach is used to determine the dynamic response of a spur gear system with uncertainty associated to gear system parameters and this uncertainty must be considered in the analysis of the dynamic behavior of this system. The simulation results are obtained by the polynomial chaos approach for dynamic analysis under uncertainty. The proposed method is an efficient probabilistic tool for uncertainty propagation. It was found to be an interesting alternative to the parametric studies. The polynomial chaos results are compared with Monte Carlo simulations.

Topological analysis of Chaos Characteristics in A Power System (전력계통의 Chaos 위상학적 특성 해석)

  • Li, S.Y.;Lee, S.S.;Li, T.Y.;Park, J.K.
    • Proceedings of the KIEE Conference
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    • 2003.11a
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    • pp.297-299
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    • 2003
  • This paper proposes a totally new method in the chaos characteristics analysis of power systems, the introduction of topological invariants. Using a return histogram the bifurcation graph was drawn, the periodic orbits and topological invariants the local crossing number, relative rotation rates, and linking number during the process of period-doubting bifurcation and chaos were extracted. This study also examined the effect on the topological invariants when the sensitive parameters were varied. In addition, the topological invariants of a three-dimensional embedding of the strange attractor was extracted and the result was compared with those obtained from differential equations. This could be a new way for a state detection and fault diagnosis in a dynamical system.

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Analysis of Flow Regimes by Using Chaos Parameters in Gas-Solid Fluidized Beds (기체-고체 유동층에서 Chaos 파라메타에 의한 흐름영역의 해석)

  • Song, Pyung-Seob;Choi, Wang-Kye;Jung, Chong-Hun;Oh, Won-Zin;Kang, Suk-Hwan;Son, Sung-Mo;Kang, Yong
    • Applied Chemistry for Engineering
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    • v.17 no.1
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    • pp.93-99
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    • 2006
  • Methods to distinguish flow regimes in gas-solid fluidized bed have been investigated by adopting the concept of chaos theory. Pressure fluctuations have been chosen as a state variable for the analysis of the system. Pressure fluctuations obtained from differential pressure transducer have been investigated using the chaos analysis (Correlation dimension and Kolmogorov entropy) as well as the average and standard deviation. As a result, fluidization regimes in gas-solid fluidized bed can be distinguished by statistics methods as the average and standard deviation. Also, Correlation dimension and Kolmogorov entropy could be used to classify the fluidization regimes.

Chaos in PID Controlled Nonlinear Systems

  • Ablay, Gunyaz
    • Journal of Electrical Engineering and Technology
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    • v.10 no.4
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    • pp.1843-1850
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    • 2015
  • Controlling nonlinear systems with linear feedback control methods can lead to chaotic behaviors. Order increase in system dynamics due to integral control and control parameter variations in PID controlled nonlinear systems are studied for possible chaos regions in the closed-loop system dynamics. The Lur’e form of the feedback systems are analyzed with Routh’s stability criterion and describing function analysis for chaos prediction. Several novel chaotic systems are generated from second-order nonlinear systems including the simplest continuous-time chaotic system. Analytical and numerical results are provided to verify the existence of the chaotic dynamics.

Identification of Chaos Phenomenon using the Classical Nonparametric Tests

  • Park, Young-Sun;Choi, Hang-Suk;Choi, Eun-Sun;Park, Moon-Il;Oh, Jae-Eung;Cha, Kyung-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.95-113
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    • 2006
  • The data resulting from a deterministic dynamic system may often appear to be random. However, it is important to distinguish a deterministic and a random processes for statistical analysis. In this paper, we propose a nonparametric test procedure to distinguish a noisy chaos from i.i.d. random process. The proposed procedure can be easily implemented by computer. We notice that the test is very effective to identify a low dimensional chaos process in some cases.

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