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Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Dynamic chaos"

1

Fang, Pan, Liming Dai, Yongjun Hou, Mingjun Du, and Wang Luyou. "The Study of Identification Method for Dynamic Behavior of High-Dimensional Nonlinear System." Shock and Vibration 2019 (March 7, 2019): 1–9. http://dx.doi.org/10.1155/2019/3497410.

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Анотація:
The dynamic behavior of nonlinear systems can be concluded as chaos, periodicity, and the motion between chaos and periodicity; therefore, the key to study the nonlinear system is identifying dynamic behavior considering the different values of the system parameters. For the uncertainty of high-dimensional nonlinear dynamical systems, the methods for identifying the dynamics of nonlinear nonautonomous and autonomous systems are treated. In addition, the numerical methods are employed to determine the dynamic behavior and periodicity ratio of a typical hull system and Rössler dynamic system, respectively. The research findings will develop the evaluation method of dynamic characteristics for the high-dimensional nonlinear system.
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2

Kumar, Deepak, and Mamta Rani. "Alternated Superior Chaotic Biogeography-Based Algorithm for Optimization Problems." International Journal of Applied Metaheuristic Computing 13, no. 1 (January 2022): 1–39. http://dx.doi.org/10.4018/ijamc.292520.

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In this study, we consider a switching strategy that yields a stable desirable dynamic behaviour when it is applied alternatively between two undesirable dynamical systems. From the last few years, dynamical systems employed “chaos1 + chaos2 = order” and “order1 + order2 = chaos” (vice-versa) to control and anti control of chaotic situations. To find parameter values for these kind of alternating situations, comparison is being made between bifurcation diagrams of a map and its alternate version, which, on their own, means independent of one another, yield chaotic orbits. However, the parameter values yield a stable periodic orbit, when alternating strategy is employed upon them. It is interesting to note that we look for stabilization of chaotic trajectories in nonlinear dynamics, with the assumption that such chaotic behaviour is not desirable for a particular situation. The method described in this paper is based on the Parrondo’s paradox, where two losing games can be alternated, yielding a winning game, in a superior orbit.
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3

Albers, D. J., J. C. Sprott, and W. D. Dechert. "Routes to Chaos in Neural Networks with Random Weights." International Journal of Bifurcation and Chaos 08, no. 07 (July 1998): 1463–78. http://dx.doi.org/10.1142/s0218127498001121.

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Neural networks are dense in the space of dynamical system. We present a Monte Carlo study of the dynamic properties along the route to chaos over random dynamical system function space by randomly sampling the neural network function space. Our results show that as the dimension of the system (the number of dynamical variables) is increased, the probability of chaos approaches unity. We present theoretical and numerical results which show that as the dimension is increased, the quasiperiodic route to chaos is the dominant route. We also qualitatively analyze the dynamics along the route.
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4

Kaneko, Kunihiko. "Chaos as a Source of Complexity and Diversity in Evolution." Artificial Life 1, no. 1_2 (October 1993): 163–77. http://dx.doi.org/10.1162/artl.1993.1.1_2.163.

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The relevance of chaos to evolution is discussed in the context of the origin and maintenance of diversity and complexity. Evolution to the edge of chaos is demonstrated in an imitation game. As an origin of diversity, dynamic clustering of identical chaotic elements, globally coupled each to the other, is briefly reviewed. The clustering is extended to nonlinear dynamics on hypercubic lattices, which enables us to construct a self-organizing genetic algorithm. A mechanism of maintenance of diversity, “homeochaos,” is given in an ecological system with interaction among many species. Homeochaos provides a dynamic stability sustained by high-dimensional weak chaos. A novel mechanism of cell differentiation is presented, based on dynamic clustering. Here, a new concept—“open chaos”—is proposed for the instability in a dynamical system with growing degrees of freedom. It is suggested that studies based on interacting chaotic elements can replace both top-down and bottom-up approaches.
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5

Egorov, Vladimir V. "Dynamic Symmetry in Dozy-Chaos Mechanics." Symmetry 12, no. 11 (November 11, 2020): 1856. http://dx.doi.org/10.3390/sym12111856.

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All kinds of dynamic symmetries in dozy-chaos (quantum-classical) mechanics (Egorov, V.V. Challenges 2020, 11, 16; Egorov, V.V. Heliyon Physics 2019, 5, e02579), which takes into account the chaotic dynamics of the joint electron-nuclear motion in the transient state of molecular “quantum” transitions, are discussed. The reason for the emergence of chaotic dynamics is associated with a certain new property of electrons, consisting in the provocation of chaos (dozy chaos) in a transient state, which appears in them as a result of the binding of atoms by electrons into molecules and condensed matter and which provides the possibility of reorganizing a very heavy nuclear subsystem as a result of transitions of light electrons. Formally, dozy chaos is introduced into the theory of molecular “quantum” transitions to eliminate the significant singularity in the transition rates, which is present in the theory when it goes beyond the Born–Oppenheimer adiabatic approximation and the Franck–Condon principle. Dozy chaos is introduced by replacing the infinitesimal imaginary addition in the energy denominator of the full Green’s function of the electron-nuclear system with a finite value, which is called the dozy-chaos energy γ. The result for the transition-rate constant does not change when the sign of γ is changed. Other dynamic symmetries appearing in theory are associated with the emergence of dynamic organization in electronic-vibrational transitions, in particular with the emergence of an electron-nuclear-reorganization resonance (the so-called Egorov resonance) and its antisymmetric (chaotic) “twin”, with direct and reverse transitions, as well as with different values of the electron–phonon interaction in the initial and final states of the system. All these dynamic symmetries are investigated using the simplest example of quantum-classical mechanics, namely, the example of quantum-classical mechanics of elementary electron-charge transfers in condensed media.
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6

Russell, David W. "Dynamic Systems & Chaos." IFAC Proceedings Volumes 31, no. 29 (October 1998): 6. http://dx.doi.org/10.1016/s1474-6670(17)38316-7.

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7

Hide, R. "Chaos in Dynamic Systems." Physics Bulletin 37, no. 9 (September 1986): 390. http://dx.doi.org/10.1088/0031-9112/37/9/034.

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8

Kana, L. K., A. Fomethe, H. B. Fotsin, E. T. Wembe, and A. I. Moukengue. "Complex Dynamics and Synchronization in a System of Magnetically Coupled Colpitts Oscillators." Journal of Nonlinear Dynamics 2017 (April 10, 2017): 1–13. http://dx.doi.org/10.1155/2017/5483956.

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Анотація:
We propose the use of a simple, cheap, and easy technique for the study of dynamic and synchronization of the coupled systems: effects of the magnetic coupling on the dynamics and of synchronization of two Colpitts oscillators (wireless interaction). We derive a smooth mathematical model to describe the dynamic system. The stability of the equilibrium states is investigated. The coupled system exhibits spectral characteristics such as chaos and hyperchaos in some parameter ranges of the coupling. The numerical exploration of the dynamics system reveals various bifurcations scenarios including period-doubling and interior crisis transitions to chaos. Moreover, various interesting dynamical phenomena such as transient chaos, coexistence of solution, and multistability (hysteresis) are observed when the magnetic coupling factor varies. Theoretical reasons for such phenomena are provided and experimentally confirmed with practical measurements in a wireless transfer.
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9

Field, Richard J. "Chaos in the Belousov–Zhabotinsky reaction." Modern Physics Letters B 29, no. 34 (December 20, 2015): 1530015. http://dx.doi.org/10.1142/s021798491530015x.

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The dynamics of reacting chemical systems is governed by typically polynomial differential equations that may contain nonlinear terms and/or embedded feedback loops. Thus the dynamics of such systems may exhibit features associated with nonlinear dynamical systems, including (among others): temporal oscillations, excitability, multistability, reaction-diffusion-driven formation of spatial patterns, and deterministic chaos. These behaviors are exhibited in the concentrations of intermediate chemical species. Bifurcations occur between particular dynamic behaviors as system parameters are varied. The governing differential equations of reacting chemical systems have as variables the concentrations of all chemical species involved, as well as controllable parameters, including temperature, the initial concentrations of all chemical species, and fixed reaction-rate constants. A discussion is presented of the kinetics of chemical reactions as well as some thermodynamic considerations important to the appearance of temporal oscillations and other nonlinear dynamic behaviors, e.g., deterministic chaos. The behavior, chemical details, and mechanism of the oscillatory Belousov–Zhabotinsky Reaction (BZR) are described. Furthermore, experimental and mathematical evidence is presented that the BZR does indeed exhibit deterministic chaos when run in a flow reactor. The origin of this chaos seems to be in toroidal dynamics in which flow-driven oscillations in the control species bromomalonic acid couple with the BZR limit cycle.
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10

Yuan, Ying Cai, Yan Li, and Yi Ming Wang. "Robust Design to Control the Chaos of Fold Mechanism with Clearance." Applied Mechanics and Materials 312 (February 2013): 153–57. http://dx.doi.org/10.4028/www.scientific.net/amm.312.153.

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Анотація:
With the increasing of web offset printing machines working speed, the nonlinear dynamics responses are more significant, even the fold mechanism with clearances appears some chaos phenomenon. Based on the dynamic model of fold mechanism, the nonlinear dynamics responses and the chaos movement in pair are studied. Used the performance parameters and dynamics response sensitivities as the goal values, the robust design model is established. By the robust design model, the nonlinear dynamic responses and chaos phenomenon can be under controlled in the same clearance degree. In this way, the performance of fold mechanism may be improved.
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Дисертації з теми "Dynamic chaos"

1

Olde, Scheper Tjeerd. "Chaos and information in dynamic neural networks." Thesis, Oxford Brookes University, 2002. https://radar.brookes.ac.uk/radar/items/e2a920c8-ff78-4ad6-adf3-8217d18c3b96/1/.

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Анотація:
This research attempts to identify and model ways to store information in dynamic, chaotic neural networks. The justification for this research is given by both biological as well as theoretical motivations [2, 27, 29, 46, 60, 107]. Firstly, there seems to be substantial support for the use of dynamic networks to study more complex and interesting behaviour. The artificial neural networks (ANN) have specific properties that define its order, such as size, type and function. Simply extending the ANN with complex non­ linear dynamics does not improve the memory performance of the network, it modifies the rate at which a global minimum may be located, if such .a state exists. Using non-linear differential equations may add more com­ plexity to the system and thereby increase the possible memory states. Secondly, even though chaos is generally undesirable, it has important properties that may be exploited to store and retrieve information [98]. These are the space filling, the possibility of control via delayed feedback, synchronization and the sensitive dependence on initial conditions. It is demonstrated in this thesis that by using delayed feedback, Unsta­ ble Periodic Orbits (UPO) may be stabilized to reduce the complexity of a chaotic system to n-periodic behaviour. This is a well known effect of de­ layed control in many types of chaotic models (e.g. Rossler equation), and the periodicity of the resulting orbit is determined by the model parameter as well as the delay (T) and the feedback strength (K) of the control func­ tion (F). Even though a theoretical infinite number of UPOs exist within a chaotic attractor only some can practically be stabilized. Furthermore, it is shown that input added to the delayed feedback controlled system allows different orbits to be stabilized. The addition of multiple delays changes the number and types of orbits that are available for stabilization. The use of synchronization between similar sets of chaotic systems may be used to target specific orbits.
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2

Ruiter, Julia. "Practical Chaos: Using Dynamical Systems to Encrypt Audio and Visual Data." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/scripps_theses/1389.

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Анотація:
Although dynamical systems have a multitude of classical uses in physics and applied mathematics, new research in theoretical computer science shows that dynamical systems can also be used as a highly secure method of encrypting data. Properties of Lorenz and similar systems of equations yield chaotic outputs that are good at masking the underlying data both physically and mathematically. This paper aims to show how Lorenz systems may be used to encrypt text and image data, as well as provide a framework for how physical mechanisms may be built using these properties to transmit encrypted wave signals.
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3

Gilbert, Francis Bertrand. "A culture of chaos: The politics of dynamic space." Diss., The University of Arizona, 1995. http://hdl.handle.net/10150/187356.

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Анотація:
This discussion of chaos theory is concerned with two major issues. On the one hand, I explore what kind of knowledge is linked to chaos theory, and more specifically how as a science it informs the cultural discourses created by postindustrial societies. On the other hand, I probe chaos theory's potential as a model for challenging the existing conception of our world within the prevailing epistemologies of order and predictability. Both of these issues are addressed with in mind the broader framework and question concerning social relations, especially to the extent that those relations, in their spatial dimension, have become an object of scientific discourse. My approach to chaos theory is purposefully eclectic, conjoining the scientific with the social and the political. I believe that chaos theory points to a dynamic, intertextual, and multidimensional universe, and therefore, my interest lies in these connections, in bridging the various elements working together to create our contemporary, postmodern world. Science creates theories and images of nature that have been used to subordinate and control segments of the population through theories of race and sexuality. Thus, to recognize the existence of complexity and instability is to give away powerful conceptual means of political and social control, a strategy in which Western science has been an active participant.
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4

Pérez, Alepuz Javier. "Dynamic visual servoing of robot manipulators: optimal framework with dynamic perceptibility and chaos compensation." Doctoral thesis, Universidad de Alicante, 2017. http://hdl.handle.net/10045/72433.

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Анотація:
This Thesis presents an optimal framework with dynamic perceptibility and chaos compensation for the control of robot manipulators. The fundamental objective of this framework is to obtain a variety of control laws for implementing dynamic visual servoing systems. In addition, this Thesis presents different contributions like the concept of dynamic perceptibility that is used to avoid image and robot singularities, the framework itself, that implements a delayed feedback controller for chaos compensation, and the extension of the framework for space robotic systems. Most of the image-based visual servoing systems implemented to date are indirect visual controllers in which the control action is joint or end-effector velocities to be applied to the robot in order to achieve a given desired location with respect to an observed object. The direct control of the motors for each joint of the robot is performed by the internal controller of the robot, which translates these velocities into joint torques. This Thesis mainly addresses the direct image-based visual servoing systems for trajectory tracking. In this case, in order to follow a given trajectory previously specified in the image space, the control action is defined as a vector of joint torques. The framework detailed in the Thesis allows for obtaining different kind of control laws for direct image-based visual servoing systems. It also integrates the dynamic perceptibility concept into the framework for avoiding image and robot singularities. Furthermore, a delayed feedback controller is also integrated so the chaotic behavior of redundant systems is compensated and thus, obtaining a smoother and efficient movement of the system. As an extension of the framework, the dynamics of free-based space systems is considered when determining the control laws, being able to determine trajectories for systems that do not have the base attached to anything. All these different steps are described throughout the Thesis. This Thesis describes in detail all the calculations for developing the visual servoing framework and the integration of the described optimization techniques. Simulation and experimental results are shown for each step, developing the controllers in an FPGA for further optimization, since this architecture allows to reduce latency and can be easily adapted for controlling of any joint robot by simply modifying certain modules that are hardware dependents. This architecture is modular and can be adapted to possible changes that may occur as a consequence of the incorporation or modification of a control driver, or even changes in the configuration of the data acquisition system or its control. This implementation, however, is not a contribution of this Thesis, but is necessary to briefly describe the architecture to understand the framework’s potential. These are the main objectives of the Thesis, and two robots where used for experimental results. A commercial industrial seven-degrees-of-freedom robot: Mitsubishi PA10, and another three-degrees-of-freedom robot. This last one’s design and implementation has been developed in the research group where the Thesis is written.
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5

Zhang, Xiaoyan. "The dynamic behaviour of road traffic flow : stability or chaos?" Thesis, Middlesex University, 1995. http://eprints.mdx.ac.uk/10685/.

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The objective of this thesis is to investigate the dynamic behaviour of road traffic flow based on theoretical traffic models. Three traffic models are examined: the classical car-following model which describes the variations of speeds of cars and distances between the cars on a road link, the logit-based trip assignment model which describes the variations of traffic flows on road links in a road network, and the dynamic gravity trip distribution model which describes the variations of flows between O-D pairs in an O-D network. Some dynamic analyses have been made of the car-following model in the literature (Chandler et al., 1958, Herman et al., 1959, Disbro & Frame, 1990, and Kirby and Smith, 1991). The dynamic gravity model and the logit-based trip assignment model are both suggested by Dendrinos and Sonis (1990) without detailed analysis. There is virtually no previous dynamic analysis of trip distribution, although there are some dynamic considerations of trip assignment based on other assignment models (Smith, 1984 and Horowitz, 1984). In this thesis, the three traffic models are considered as dynamical systems. The variations of traffic characteristics are investigated in the context of nonlinear dynamics. Equilibria and oscillatory behaviour are found in all three traffic models; complicated behaviour including period doubling and chaos is found in the gravity model. Values of parameters for different types of behaviour in the models are given. Conditions for the stability of equilibria in the models are established. The stability analysis of the equilibrium in the car-following model is more general here than that in the literature (Chandler et al., 1958, Herman et al., 1959). Chaotic attractors found in the gravity model are characterized by Liapunov exponents and fractal dimension. The research in this thesis aims at understanding and predicting traffic behaviour under various conditions. Traffic systems may be monitored, based on these results, to achieve a stable equilibrium and to avoid instabilities and chaos.
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6

Machekhin, Yu P. "Uncertainty measurement and dynamic system chaotical behaviour." Thesis, France, 2008. http://openarchive.nure.ua/handle/document/8734.

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Chaotic behaviour of nonlinear dynamic system as a mechanism of influence on uncertainty measurement are discussed. Based on the logistic equation as a mathematical models of measeurement uncertainty investigated as a function of state of dynamic system. In the case when dynamic chaos take place in system, uncertainty measurement are increasing and has anormal distribution.
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7

Fisher, James Robert. "Stability analysis and control of stochastic dynamic systems using polynomial chaos." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2853.

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8

Taylor, Imogen T. F. "Control and synchronisation of coupled map lattices : interdisciplinary modelling of synchronised dynamic behaviour (insects in particular)." Thesis, University of Derby, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275687.

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9

Lee, Hyunwook. "A Polynomial Chaos Approach for Stochastic Modeling of Dynamic Wheel-Rail Friction." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77195.

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Анотація:
Accurate estimation of the coefficient of friction (CoF) is essential to accurately modeling railroad dynamics, reducing maintenance costs, and increasing safety factors in rail operations. The assumption of a constant CoF is popularly used in simulation studies for ease of implementation, however many evidences demonstrated that CoF depends on various dynamic parameters and instantaneous conditions. In the real world, accurately estimating the CoF is difficult due to effects of various uncertain parameters, such as wheel and rail materials, rail roughness, contact patch, and so on. In this study, the newly developed 3-D nonlinear CoF model for the dry rail condition is introduced and the CoF variation is tested using this model with dynamic parameters estimated from the wheel-rail simulation model. In order to account for uncertain parameters, a stochastic analysis using the polynomial chaos (poly-chaos) theory is performed using the CoF and wheel-rail dynamics models. The wheel-rail system at a right traction wheel is modeled as a mass-spring-damper system to simulate the basic wheel-rail dynamics and the CoF variation. The wheel-rail model accounts for wheel-rail contact, creepage effect, and creep force, among others. Simulations are performed at train speed of 20 m/s for 4 sec using rail roughness as a unique excitation source. The dynamic simulation has been performed for the deterministic model and for the stochastic model. The dynamics results of the deterministic model provide the starting point for the uncertainty analysis. Six uncertain parameters have been studied with an assumption of 50% uncertainty, intentionally imposed for testing extreme conditions. These parameters are: the maximum amplitude of rail roughness (MARR), the wheel lateral displacement, the track stiffness and damping coefficient, the sleeper distance, and semi-elliptical contact lengths. A symmetric beta distribution is assumed for these six uncertain parameters. The PDF of the CoF has been obtained for each uncertain parameter study, for combinations of two different uncertain parameters, and also for combinations of three different uncertain parameters. The results from the deterministic model show acceptable vibration results for the body, the wheel, and the rail. The introduced CoF model demonstrates the nonlinear variation of the total CoF, the stick component, and the slip component. In addition, it captures the maximum CoF value (initial peak) successfully. The stochastic analysis results show that the total CoF PDF before 1 sec is dominantly affected by the stick phenomenon, while the slip dominantly influences the total CoF PDF after 1 sec. Although a symmetric distribution has been used for the uncertain parameters considered, the uncertainty in the response obtained displayed a skewed distribution for some of the situations investigated. The CoF PDFs obtained from simulations with combinations of two and three uncertain parameters have wider PDF ranges than those obtained for only one uncertain parameter. FFT analysis using the rail displacement has been performed for the qualitative validation of the stochastic simulation result due to the absence of the experimental data. The FFT analysis of the deterministic rail displacement and of the stochastic rail displacement with uncertainties demonstrates consistent trends commensurate with loss of tractive efficiency, such as the bandwidth broadening, peak frequency shifts, and side band occurrence. Thus, the FFT analysis validates qualitatively that the stochastic modeling with various uncertainties is well executed and is reflecting observable, real-world results. In conclusions, the development of an effective model which helps to understand the nonlinear nature of wheel-rail friction is critical to the progress of railroad component technology and rail safety. In the real world, accurate estimation of the CoF at the wheel-rail interface is very difficult since it is influenced by several uncertain parameters as illustrated in this study. Using the deterministic CoF value can cause underestimation or overestimation of CoF values leading to inaccurate decisions in the design of the wheel-rail system. Thus, the possible PDF ranges of the CoF according to key uncertain parameters must be considered in the design of the wheel-rail system.
Ph. D.
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10

ELPHICK, CHRISTIAN. "Formes normales, defauts topologiques et chaos spatial." Nice, 1987. http://www.theses.fr/1987NICE4160.

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La 1ere partie de cette these regroupe des travaux sur la reduction a la forme normale des equations differentielles ordinaires. Dans le 1er travail de cette partie une simple caracterisation globale des formes normales des champs vectoriels singuliers est donnee. Les autres travaux sont consacres a l'etude de la reduction a la forme normale quand on ajoute des perturbations periodiques ou stochastiques a nos sequations differentielles et dans le cas ou le systeme physique est decrit par un ensemble des variables de grassmann(systeme de fermi classique). Dans la 2eme partie on regroupe des travaux sur les formes normales dans un systeme etendu. En particulier on etudie la linearisation de l'equation non-lineaire de schroedinger pour un champ bosonique et le cas de la convection du type rayleigh-benard soumis a une modulation spatiale exterieure. Enfin, la 3eme partie est constituee par des travaux sur les defauts topologiques, les mecanismes de chaos spatial dans des systemes macroscopiques et sur une version de la theorie de melnikov utilisee pour trouver la dynamique de ces defauts
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Книги з теми "Dynamic chaos"

1

Zaslavskiĭ, G. M. Chaos in dynamic systems. Chur: Harwood Academic, 1985.

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2

Chaos in dynamic systems. Chur: Harwood Academic Publishers, 1985.

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3

Faghih, Nezameddin. Chaos and Fractals in Dynamic Systems. Tehran: University of Technology, 2003.

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4

T. V. S. M. olde Scheper. Chaos and information in dynamic neural networks. Oxford: Oxford Brookes University, 2002.

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5

G, Malliaris A., ed. Differential equations, stability, and chaos in dynamic economics. Amsterdam: North-Holland, 1989.

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6

Geert, Paul van. Dynamic systems of development: Change between complexity and chaos. New York: Harvester Wheatsheaf, 1994.

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7

The dynamic nature of ecosystems: Chaos and order entwined. Chichester: Wiley, 1995.

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8

The art of modeling dynamic systems: Forecasting for chaos, randomness, and determinism. New York: Wiley, 1991.

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9

Friedman, Lisa. The dynamic enterprise: Tools for turning chaos into strategy and strategy into action. San Francisco, Calif: Jossey-Bass, 1998.

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10

1943-, Jodl H. J., ed. Chaos: A program collection for the PC. 2nd ed. Berlin: Springer, 1999.

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Частини книг з теми "Dynamic chaos"

1

Hannon, Bruce, and Matthias Ruth. "Chaos." In Dynamic Modeling, 219–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-662-25989-4_31.

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2

Hannon, Bruce, and Matthias Ruth. "Chaos." In Dynamic Modeling, 219–26. New York, NY: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4684-0224-7_31.

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3

Hannon, Bruce, and Matthias Ruth. "Chaos." In Dynamic Modeling, 376–84. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0211-7_37.

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4

Martynov, Georgy A. "Chaos in dynamic systems." In Classical Statistical Mechanics, 3–26. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8963-5_1.

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Mitra, Tapan. "Introduction to Dynamic Optimization Theory." In Optimization and Chaos, 31–108. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04060-7_2.

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Ruth, Matthias, and Bruce Hannon. "Preference Cycles and Chaos." In Modeling Dynamic Economic Systems, 291–97. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2209-9_29.

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Ruth, Matthias, and Bruce Hannon. "Chaos in Macroeconomic Models." In Modeling Dynamic Economic Systems, 311–15. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2209-9_32.

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Ruth, Matthias, and Bruce Hannon. "Preference Cycles and Chaos." In Modeling Dynamic Economic Systems, 285–91. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2268-2_29.

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Ruth, Matthias, and Bruce Hannon. "Chaos in Macroeconomic Models." In Modeling Dynamic Economic Systems, 304–7. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2268-2_32.

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Cordes-Berszinn, Philip. "Organizational Structures — Configurations between Chaos and Order." In Dynamic Capabilities, 94–148. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137351289_3.

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Тези доповідей конференцій з теми "Dynamic chaos"

1

Rios Leite, José R. "Characterizing Bifurcations by Averages of Chaotic Dynamic Variables." In EXPERIMENTAL CHAOS: 7th Experimental Chaos Conference. AIP, 2003. http://dx.doi.org/10.1063/1.1612241.

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2

Livne, Ariel. "Universal Aspects of Dynamic Fracture in Brittle Materials." In EXPERIMENTAL CHAOS: 8th Experimental Chaos Conference. AIP, 2004. http://dx.doi.org/10.1063/1.1846468.

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3

Larger, Laurent. "Sub-critical Hopf bifurcation in a time-delayed differential dynamic." In EXPERIMENTAL CHAOS: 7th Experimental Chaos Conference. AIP, 2003. http://dx.doi.org/10.1063/1.1612200.

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4

Corron, Ned J. "Dynamic Limiter Control of Long-Period Orbits and Arbitrary Trajectories in an Electronic Circuit." In EXPERIMENTAL CHAOS: 7th Experimental Chaos Conference. AIP, 2003. http://dx.doi.org/10.1063/1.1612238.

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5

Oraevsky, Anatoly N. "Dynamics of single-mode lasers and dynamic chaos." In Nonlinear Dynamics of Laser and Optical Systems, edited by Valery V. Tuchin. SPIE, 1997. http://dx.doi.org/10.1117/12.276179.

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SKOWRONSKI, J., W. GRANTHAM, and B. LEE. "Use of chaos in dynamic game." In Guidance, Navigation and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-3600.

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Kushnir, N. Ya, P. P. Horley, and A. N. Grygoryshyn. "Dynamic chaos in phase synchronization devices." In 2005 15th International Crimean Conference Microwave and Telecommunication Technology. IEEE, 2005. http://dx.doi.org/10.1109/crmico.2005.1564936.

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Belej, Olexander, Tamara Lohutova, and Marian Banas. "Algorithm for Image Transfer Using Dynamic Chaos." In 2019 IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM). IEEE, 2019. http://dx.doi.org/10.1109/cadsm.2019.8779285.

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Liu, Bo, Jiancheng Zou, and Jianwen Wang. "Flocking of Multiple Dynamic Agents." In 2009 International Workshop on Chaos-Fractals Theories and Applications (IWCFTA). IEEE, 2009. http://dx.doi.org/10.1109/iwcfta.2009.36.

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Lu, Ya-Li, Hui-Feng Xue, and Zhan-Guo Li. "Chaos Control of an Dynamic Output Game Model." In 2007 3rd International Conference on Wireless Communications, Networking, and Mobile Computing - WiCOM '07. IEEE, 2007. http://dx.doi.org/10.1109/wicom.2007.1407.

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Звіти організацій з теми "Dynamic chaos"

1

Battaglini, Marco. Chaos and Unpredictability in Dynamic Social Problems. Cambridge, MA: National Bureau of Economic Research, January 2021. http://dx.doi.org/10.3386/w28347.

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2

Perdigão, Rui A. P. New Horizons of Predictability in Complex Dynamical Systems: From Fundamental Physics to Climate and Society. Meteoceanics, October 2021. http://dx.doi.org/10.46337/211021.

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Анотація:
Discerning the dynamics of complex systems in a mathematically rigorous and physically consistent manner is as fascinating as intimidating of a challenge, stirring deeply and intrinsically with the most fundamental Physics, while at the same time percolating through the deepest meanders of quotidian life. The socio-natural coevolution in climate dynamics is an example of that, exhibiting a striking articulation between governing principles and free will, in a stochastic-dynamic resonance that goes way beyond a reductionist dichotomy between cosmos and chaos. Subjacent to the conceptual and operational interdisciplinarity of that challenge, lies the simple formal elegance of a lingua franca for communication with Nature. This emerges from the innermost mathematical core of the Physics of Coevolutionary Complex Systems, articulating the wealth of insights and flavours from frontier natural, social and technical sciences in a coherent, integrated manner. Communicating thus with Nature, we equip ourselves with formal tools to better appreciate and discern complexity, by deciphering a synergistic codex underlying its emergence and dynamics. Thereby opening new pathways to see the “invisible” and predict the “unpredictable” – including relative to emergent non-recurrent phenomena such as irreversible transformations and extreme geophysical events in a changing climate. Frontier advances will be shared pertaining a dynamic that translates not only the formal, aesthetical and functional beauty of the Physics of Coevolutionary Complex Systems, but also enables and capacitates the analysis, modelling and decision support in crucial matters for the environment and society. By taking our emerging Physics in an optic of operational empowerment, some of our pioneering advances will be addressed such as the intelligence system Earth System Dynamic Intelligence and the Meteoceanics QITES Constellation, at the interface between frontier non-linear dynamics and emerging quantum technologies, to take the pulse of our planet, including in the detection and early warning of extreme geophysical events from Space.
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Stewart, H. B. Chaos, dynamical structure and climate variability. Office of Scientific and Technical Information (OSTI), September 1995. http://dx.doi.org/10.2172/102163.

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4

Harrison, Robert G. Dynamical Instabilities, Chaos And Spatial Complexity In Fundamental Nonlinear Optical Interactions. Fort Belvoir, VA: Defense Technical Information Center, May 1994. http://dx.doi.org/10.21236/ada291223.

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JAMES, DANIEL F. DYNAMICAL STABILITY AND QUANTUM CHAOS OF IONS IN A LINEAR TRAP (1999002ER). Office of Scientific and Technical Information (OSTI), September 2002. http://dx.doi.org/10.2172/801242.

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6

Oh, Y. G., N. Sreenath, P. S. Krishnaprasad, and J. E. Marsden. The Dynamics of Coupled Planar Rigid Bodies. Part 2. Bifurcations, Periodic Solutions, and Chaos. Fort Belvoir, VA: Defense Technical Information Center, January 1988. http://dx.doi.org/10.21236/ada452393.

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7

Perdigão, Rui A. P. Unveiling Order beneath Climatic Change Chaos in the light of Coevolutionary Complex System Dynamics. Meteoceanics, April 2021. http://dx.doi.org/10.46337/210407.

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8

Li, Yongjun, Jinyu Wan, Allen Liu, Yi Jiao, and Robert Rainer. Data-driven Chaos Indicator for Nonlinear Dynamics and Applications on Storage Ring Lattice Design. Office of Scientific and Technical Information (OSTI), November 2021. http://dx.doi.org/10.2172/1834604.

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9

Schmidt, G. Investigations of transitions from order to chaos in dynamical systems. Annual progress report. Office of Scientific and Technical Information (OSTI), March 1993. http://dx.doi.org/10.2172/10157816.

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Meiss, J. D., P. J. Morrison, and J. Tennyson. Summary of the 1991 ACP Workshop on Coherence and Chaos in Complex Dynamical Systems. Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada243226.

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