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Author: Kurths, Jürgen × DDC: 510 × Type: article ×

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Now showing 1 - 5 of 5
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    Predicting the data structure prior to extreme events from passive observables using echo state network
    (Lausanne : Frontiers Media, 2022) Banerjee, Abhirup; Mishra, Arindam; Dana, Syamal K.; Hens, Chittaranjan; Kapitaniak, Tomasz; Kurths, Jürgen; Marwan, Norbert
    Extreme events are defined as events that largely deviate from the nominal state of the system as observed in a time series. Due to the rarity and uncertainty of their occurrence, predicting extreme events has been challenging. In real life, some variables (passive variables) often encode significant information about the occurrence of extreme events manifested in another variable (active variable). For example, observables such as temperature, pressure, etc., act as passive variables in case of extreme precipitation events. These passive variables do not show any large excursion from the nominal condition yet carry the fingerprint of the extreme events. In this study, we propose a reservoir computation-based framework that can predict the preceding structure or pattern in the time evolution of the active variable that leads to an extreme event using information from the passive variable. An appropriate threshold height of events is a prerequisite for detecting extreme events and improving the skill of their prediction. We demonstrate that the magnitude of extreme events and the appearance of a coherent pattern before the arrival of the extreme event in a time series affect the prediction skill. Quantitatively, we confirm this using a metric describing the mean phase difference between the input time signals, which decreases when the magnitude of the extreme event is relatively higher, thereby increasing the predictability skill.
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    How Price-Based Frequency Regulation Impacts Stability in Power Grids: A Complex Network Perspective
    (London : Hindawi, 2020) Ji, Peng; Zhu, Lipeng; Lu, Chao; Lin, Wei; Kurths, Jürgen
    With the deregulation of modern power grids, electricity markets are playing a more and more important role in power grid operation and control. However, it is still questionable how the real-time electricity price-based operation affects power grid stability. From a complex network perspective, here we investigate the dynamical interactions between price-based frequency regulations and physical networks, which results in an interesting finding that a local minimum of network stability occurs when the response strength of generators/consumers to the varying price increases. A case study of the real world-based China Southern Power Grid demonstrates the finding and exhibits a feasible approach to network stability enhancement in smart grids. This also provides guidance for potential upgrade and expansion of the current power grids in a cleaner and safer way. © 2020 Peng Ji et al.
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    Systems Medicine of Cancer: Bringing Together Clinical Data and Nonlinear Dynamics of Genetic Networks
    (London : Hindawi, 2016) Blyuss, Konstantin B.; Manchanda, Ranjit; Kurths, Jürgen; Alsaedi, Ahmed; Zaikin, Alexey
    Editorial
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    Fixed-Time Connectivity Preserving Tracking Consensus of Multiagent Systems with Disturbances
    (London : Hindawi, 2020) Sun, Fenglan; Liu, Peiyong; Kurths, Jürgen; Zhu, Wei
    This text studies the fixed-time tracking consensus for nonlinear multiagent systems with disturbances. To make the fixed-time tracking consensus, the distributed control protocol based on the integral sliding mode control is proposed; meanwhile, the adjacent followers can be maintained in a limited sensing range. By using the nonsmooth analysis method, sufficient conditions for the fixed-time consensus together with the upper and lower bounds of convergence time are obtained. An example is given to illustrate the potential correctness of the main results. © 2020 Fenglan Sun et al.
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    Novel fixed-time stabilization of quaternion-valued BAMNNs with disturbances and time-varying coefficients
    (Springfield, MO : AIMS Press, 2020) Wei, Ruoyu; Cao, Jinde; Kurths, Jürgen
    In this paper, with the quaternion number and time-varying coefficients introduced into traditional BAMNNs, the model of quaternion-valued BAMNNs are formulated. For the first time, fixed-time stabilization of time-varying quaternion-valued BAMNNs is investigated. A novel fixed-time control method is adopted, in which the choice of the Lyapunov function is more general than in most previous results. To cope with the noncommutativity of the quaternion multiplication, two different fixed-time control methods are provided, a decomposition method and a non-decomposition method. Furthermore, to reduce the control strength and improve control efficiency, an adaptive fixed-time control strategy is proposed. Lastly, numerical examples are presented to demonstrate the effectiveness of the theoretical results. © 2020 the Author(s), licensee AIMS Press.