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Relevant bibliographies by topics / Spatio-temporal dynamical systems

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Academic literature on the topic 'Spatio-temporal dynamical systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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Journal articles on the topic "Spatio-temporal dynamical systems"

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Uhl, C., F. Kruggel, and D. Y. von Cramon. "Dynamical Systems Based Spatio-Temporal EEG/MEG Modeling." NeuroImage 7, no. 4 (May 1998): S675. http://dx.doi.org/10.1016/s1053-8119(18)31508-8.

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Rod, D. L., and B. D. Sleeman. "Complexity in spatio-temporal dynamics." Proceedings of the Royal Society of Edinburgh: Section A Mathematics 125, no. 5 (1995): 959–74. http://dx.doi.org/10.1017/s0308210500022587.

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Complex and chaotic structures in certain dynamical systems in biology arise as a consequence of noncomplete integrability of two-degree-of-freedom Hamiltonian systems. A study of this problem is made using Ziglin theory and implemented with the aid of the Kovacic algorithm.

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GUO, YUZHU, L. Z. GUO, S. A. BILLINGS, DANIEL COCA, and Z. Q. LANG. "CHARACTERIZING NONLINEAR SPATIO-TEMPORAL SYSTEMS IN THE FREQUENCY DOMAIN." International Journal of Bifurcation and Chaos 22, no. 02 (February 2012): 1230009. http://dx.doi.org/10.1142/s0218127412300091.

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In this paper a new concept, spatio-temporal generalized frequency response functions (STGFRF), is introduced for the first time to characterize nonlinear spatio-temporal dynamical systems in the frequency domain. A probing method is developed to calculate the STGFRFs recursively for both continuous and discrete spatio-temporal systems. The algorithm is computationally compact and exposes the explicit relationship between the continuous and discrete models and the elements of the generalized frequency response functions.

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Guo, L. Z., and S. A. Billings. "Identification and analysis of spatio-temporal dynamical systems using wavelets." International Journal of Systems Science 39, no. 3 (March 2008): 315–34. http://dx.doi.org/10.1080/00207720701806089.

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DAYA SAGAR, B. S., and C. BABU RAO. "EDITORIAL." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 02 (March 2003): 163–65. http://dx.doi.org/10.1142/s0218001403002289.

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Natural systems undergo several morphological changes with time. To study spatio-temporal dynamics of such natural systems, and to further understand the morphological dynamical behaviors, various images that show several macro- and micro-level phenomena, acquired by various types of sensors need to be analyzed in spatio-temporal scales. Such analyses, to facilitate the researcher to model the spatio-temporal organization of a desired phenomenon, evidently require the robust procedures to extract specific error-free features from multiscale-temporal images represented in discrete space. Geometry and topology based features, such as edges of unique type and general type, are the indicators to record the changes that occur temporally. Extraction of such information is essential prerequisite to develop cogent models to understand the spatio-temporal organization.

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McDermott, Patrick, and Christopher Wikle. "Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data." Entropy 21, no. 2 (February 15, 2019): 184. http://dx.doi.org/10.3390/e21020184.

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Recurrent neural networks (RNNs) are nonlinear dynamical models commonly used in the machine learning and dynamical systems literature to represent complex dynamical or sequential relationships between variables. Recently, as deep learning models have become more common, RNNs have been used to forecast increasingly complicated systems. Dynamical spatio-temporal processes represent a class of complex systems that can potentially benefit from these types of models. Although the RNN literature is expansive and highly developed, uncertainty quantification is often ignored. Even when considered, the uncertainty is generally quantified without the use of a rigorous framework, such as a fully Bayesian setting. Here we attempt to quantify uncertainty in a more formal framework while maintaining the forecast accuracy that makes these models appealing, by presenting a Bayesian RNN model for nonlinear spatio-temporal forecasting. Additionally, we make simple modifications to the basic RNN to help accommodate the unique nature of nonlinear spatio-temporal data. The proposed model is applied to a Lorenz simulation and two real-world nonlinear spatio-temporal forecasting applications.

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Guo, Lingzhong, and Stephen A. Billings. "State-Space Reconstruction and Spatio-Temporal Prediction of Lattice Dynamical Systems." IEEE Transactions on Automatic Control 52, no. 4 (April 2007): 622–32. http://dx.doi.org/10.1109/tac.2007.894513.

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ITOH, MAKOTO, and LEON O. CHUA. "OSCILLATIONS ON THE EDGE OF CHAOS VIA DISSIPATION AND DIFFUSION." International Journal of Bifurcation and Chaos 17, no. 05 (May 2007): 1531–73. http://dx.doi.org/10.1142/s0218127407018336.

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The primary purpose of this paper is to show that simple dissipation can bring about oscillations in certain kinds of asymptotically stable nonlinear dynamical systems; namely when the system is locally active where the dissipation is introduced. Furthermore, if these nonlinear dynamical systems are coupled with appropriate choice of diffusion coefficients, then the coupled system can exhibit spatio-temporal oscillations. The secondary purpose of this paper is to show that spatio-temporal oscillations can occur in spatially discrete reaction diffusion equations operating on the edge of chaos, provided the array size is sufficiently large.

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GUO, YUZHU, STEVE A. BILLINGS, and DANIEL COCA. "IDENTIFICATION OF n-STATE SPATIO-TEMPORAL DYNAMICAL SYSTEMS USING A POLYNOMIAL MODEL." International Journal of Bifurcation and Chaos 18, no. 07 (July 2008): 2049–57. http://dx.doi.org/10.1142/s0218127408021543.

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A multivariable polynomial model is introduced to describe n-state spatio-temporal systems. Based on this model, a new neighborhood detection and transition rules determination method is proposed. Simulation results illustrate that the new method performs well even when the patterns are corrupted by static and dynamical noise.

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Guo, L. Z., S. A. Billings, and H. L. Wei. "Estimation of spatial derivatives and identification of continuous spatio-temporal dynamical systems." International Journal of Control 79, no. 9 (September 2006): 1118–35. http://dx.doi.org/10.1080/00207170600804050.

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Dissertations / Theses on the topic "Spatio-temporal dynamical systems"

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Campbell, Kevin Matthew. "The robust and typical behaviour of spatio-temporal dynamical systems." Thesis, University of Warwick, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309905.

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Guo, Yuzhu. "The Identification and Analysis of Finite-State Spatio-Temporal Dynamical Systems." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.522004.

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Orstavik, Odd-Halvdan Sakse. "Analysis of chaotic multi-variate time-series from spatio-temporal dynamical systems." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314071.

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Siminos, Evangelos. "Recurrent spatio-temporal structures in presence of continuous symmetries." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28215.

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Thesis (M. S.)--Physics, Georgia Institute of Technology, 2009.
Committee Chair: Cvitanovic, Predrag; Committee Member: Dieci, Luca; Committee Member: Grigoriev, Roman; Committee Member: Schatz, Michael; Committee Member: Wiesenfeld, Kurt

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MacKenzie, Tony. "Create accurate numerical models of complex spatio-temporal dynamical systems with holistic discretisation." University of Southern Queensland, Faculty of Sciences, 2005. http://eprints.usq.edu.au/archive/00001466/.

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This dissertation focuses on the further development of creating accurate numerical models of complex dynamical systems using the holistic discretisation technique [Roberts, Appl. Num. Model., 37:371-396, 2001]. I extend the application from second to fourth order systems and from only one spatial dimension in all previous work to two dimensions (2D). We see that the holistic technique provides useful and accurate numerical discretisations on coarse grids. We explore techniques to model the evolution of spatial patterns governed by pdes such as the Kuramoto-Sivashinsky equation and the real-valued Ginzburg-Landau equation. We aim towards the simulation of fluid flow and convection in three spatial dimensions. I show that significant steps have been taken in this dissertation towards achieving this aim. Holistic discretisation is based upon centre manifold theory [Carr, Applications of centre manifold theory, 1981] so we are assured that the numerical discretisation accurately models the dynamical system and may be constructed systematically. To apply centre manifold theory the domain is divided into elements and using a homotopy in the coupling parameter, subgrid scale fields are constructed consisting of actual solutions of the governing partial differential equation(pde). These subgrid scale fields interact through the introduction of artificial internal boundary conditions. View the centre manifold (macroscale) as the union of all states of the collection of subgrid fields (microscale) over the physical domain. Here we explore how to extend holistic discretisation to the fourth order Kuramoto-Sivashinsky pde. I show that the holistic models give impressive accuracy for reproducing the steady states and time dependent phenomena of the Kuramoto-Sivashinsky equation on coarse grids. The holistic method based on local dynamics compares favourably to the global methods of approximate inertial manifolds. The excellent performance of the holistic models shown here is strong evidence in support of the holistic discretisation technique. For shear dispersion in a 2D channel a one-dimensional numerical approximation is generated directly from the two-dimensional advection-diffusion dynamics. We find that a low order holistic model contains the shear dispersion term of the Taylor model [Taylor, IMA J. Appl. Math., 225:473-477, 1954]. This new approach does not require the assumption of large x scales, formerly absolutely crucial in deriving the Taylor model. I develop holistic discretisation for two spatial dimensions by applying the technique to the real-valued Ginzburg-Landau equation as a representative example of second order pdes. The techniques will apply quite generally to second order reaction-diffusion equations in 2D. This is the first study implementing holistic discretisation in more than one spatial dimension. The previous applications of holistic discretisation have developed algebraic forms of the subgrid field and its evolution. I develop an algorithm for numerical construction of the subgrid field and its evolution for 1D and 2D pdes and explore various alternatives. This new development greatly extends the class of problems that may be discretised by the holistic technique. This is a vital step for the application of the holistic technique to higher spatial dimensions and towards discretising the Navier-Stokes equations.

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Dufourd, Claire Chantal. "Spatio-temporal mathematical models of insect trapping : analysis, parameter estimation and applications to control." Thesis, University of Pretoria, 2016. http://hdl.handle.net/2263/58471.

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This thesis provides a mathematical framework for the development of efficient control strategies that satisfy the charters of Integrated Pest Management (IPM) which aims to maintain pest population at a low impact level. This mathematical framework is based on a dynamical system approach and comprises the construction of mathematical models, their theoretical study, the development of adequate schemes for numerical solutions and reliable procedures for parameter identification. The first output of this thesis is the construction of trap-insect spatio-temporal models formulated via advection-diffusion-reaction processes. These models were used to simulate numerically trapping to compare with field data. As a result, practical protocols were identified to estimate pest-population size and distribution as well as its dispersal capacity and parameter values related to the attractiveness of the traps. The second major output of this thesis is the prediction of the impact of a specific control method: mating disruption using a female pheromone and trapping. A compartmental model, formulated via a system of ordinary differential equations, was built based on biological and mating behaviour knowledge of the pest. The theoretical analysis of the model yields threshold values for the dosage of the pheromone above which extinction of the population is ensured. The practical relevance of the results obtained in this thesis shows that mathematical modelling is an essential supplement to experiments in optimizing control strategies.
Thesis (PhD)--University of Pretoria, 2016.
Mathematics and Applied Mathematics
PhD
Unrestricted

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Kurtuldu, Huseyin. "New methods of characterizing spatio-temporal patterns in laboratory experiments." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37121.

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Complex patterns arise in many extended nonlinear nonequilibrium systems in physics, chemistry and biology. Information extraction from these complex patterns is a challenge and has been a main subject of research for many years. We study patterns in Rayleigh-Benard convection (RBC) acquired from our laboratory experiments to develop new characterization techniques for complex spatio-temporal patterns. Computational homology, a new topological characterization technique, is applied to the experimental data to investigate dynamics by quantifying convective patterns in a unique way. The homology analysis is used to detect symmetry breakings between hot and cold flows as a function of thermal driving in experiments, where other conventional techniques, e.g., curvature and wave-number distribution, failed to reveal this asymmetry. Furthermore, quantitative information is acquired from the outputs of homology to identify different spatio-temporal states. We use this information to obtain a reduced dynamical description of spatio-temporal chaos to investigate extensivity and physical boundary effects in RBC. The results from homological analysis are also compared to other dimensionality reduction techniques such as Karhunen-Loeve decomposition and Fourier analysis.

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Lan, Yueheng. "Dynamical systems approach to one-dimensional spatiotemporal chaos -- A cyclist's view." Diss., Available online, Georgia Institute of Technology, 2004:, 2004. http://etd.gatech.edu/theses/available/etd-10282004-154606/unrestricted/lan%5Fyueheng%5F200412%5Fphd.pdf.

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Thesis (Ph. D.)--Physics, Georgia Institute of Technology, 2005.
Jean Bellissard, Committee Member ; Turgay Uzer, Committee Member ; Roman Grigoriev, Committee Member ; Konstantin Mischaikow, Committee Member ; Predrag Cvitanovic, Committee Chair. Vita. Includes bibliographical references.

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Krishan, Kapilanjan. "Characterizations of spatio-temporal complex systems." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-05162005-071906/.

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Thesis (Ph. D.)--Physics, Georgia Institute of Technology, 2006.
Schatz, Michael, Committee Chair ; Cvitanovic, Predrag, Committee Member ; Uzer, Turgay, Committee Member ; Grigoriev, Roman, Committee Member ; Mischaikow, Konstantin, Committee Member.

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Goryachev, Andrew. "Spatio-temporal dynamics of complex-periodic and chaotic systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0002/NQ41163.pdf.

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Books on the topic "Spatio-temporal dynamical systems"

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Campbell, Kevin Matthew. The robust and typical behaviour of spatio-temporal dynamical systems. [s.l.]: typescript, 1996.

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Schöll, E. Nonlinear spatio-temporal dynamics and chaos in semiconductors. Cambridge, UK: Cambridge University Press, 2001.

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NATO Advanced Research Workshop on Nonlinear Evolution of Spatio-Temporal Structures in Dissipative Continuous Systems (1989 Streitberg, Wiesenttal, Germany). Nonlinear evolution of spatio-temporal structures in dissipative continuous systems. New York: Plenum Press, 1990.

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Gundlach, Volker Matthias. Symbolic dynamics, shadowing and Gibbs states for some spatio-temporal chaotic systems. [s.l.]: typescript, 1991.

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Center for Nonlinear Studies. Conference. Spatio-temporal coherence and chaos in physical systems: Los Alamos Center for Nonlinear Studies Workshop, January 21-24, 1986. Edited by Bishop Alan R. 1947-, Grüner George, and Nicolaenko Basil 1943-. Amsterdam: North-Holland, 1986.

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Innocent, Mutabazi, Wesfreid J. E, and Guyon Etienne, eds. Dynamics of spatio-temporal cellular structures. New York: Springer, 2005.

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Goryachev, Andrew. Spatio-temporal dynamics of complex-periodic and chaotic: Systems. Dept of Chemistry, U of Toronto, 1999.

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Schöll, Eckehard. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors. Cambridge University Press, 2001.

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Busse, F. H. Nonlinear Evolution of Spatio-Temporal Structures in Dissipative Continuous Systems. Springer, 2012.

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Guyon, Etienne, Innocent Mutabazi, and Jose Eduardo Wesfreid. Dynamics of Spatio-Temporal Cellular Structures: Henri Bénard Centenary Review. Springer, 2014.

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Book chapters on the topic "Spatio-temporal dynamical systems"

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Uhl, Christian, and Rudolf Friedrich. "Spatio-Temporal Modeling Based on Dynamical Systems Theory." In Springer Series in Synergetics, 274–305. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60007-4_15.

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Dahlem, Markus A., Thomas Mair, and Stefan C. Müller. "Spatio-Temporal Aspects of a Dynamical Disease: Waves of Spreading Depression." In Function and Regulation of Cellular Systems, 421–34. Basel: Birkhäuser Basel, 2004. http://dx.doi.org/10.1007/978-3-0348-7895-1_42.

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Pomeau, Yves. "Rayleigh-Bénard Convection as a Model of a Nonlinear System: A Personal View." In Dynamics of Spatio-Temporal Cellular Structures, 95–102. New York, NY: Springer New York, 2006. http://dx.doi.org/10.1007/978-0-387-25111-0_5.

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Leppänen, T., M. Karttunen, R. A. Barrio, and K. Kaski. "Spatio-temporal dynamics in a Turing model." In Unifying Themes in Complex Systems, 215–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17635-7_26.

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Aon, M. A., and S. Cortassa. "Dynamic coupling and spatio–temporal coherence in cellular systems." In Dynamic Biological Organization, 430–84. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5828-2_12.

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Hikihara, Takashi, Yoshinobu Okamoto, and Yoshisuke Ueda. "Spatio-Temporal Dynamics of Coupled Magneto-Elastic System." In IUTAM Symposium on New Applications of Nonlinear and Chaotic Dynamics in Mechanics, 523–31. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-5320-1_52.

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Gehrig, Edeltraud, and Ortwin Hess. "Spatio-Spectral Wave Mixing in High-Power Amplifier and Laser Systems." In Spatio-Temporal Dynamics and Quantum Fluctuations in Semiconductor Lasers, 113–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36558-7_7.

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Litvak, A. G., V. A. Mironov, and A. M. Sergeev. "The Nonlinear Dynamics of Wave Systems with Spatio-Temporal Collapses." In Nonlinear Waves 3, 240–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75308-4_22.

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Rafajłowicz, Ewaryst, and Wojciech Rafajłowicz. "D-Optimum Input Signals for Systems with Spatio-Temporal Dynamics." In Contributions to Statistics, 219–27. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00218-7_26.

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Sánchez-Morcillo, V. J., N. Jiménez, J. Chaline, A. Bouakaz, and S. Dos Santos. "Spatio-Temporal Dynamics in a Ring of Coupled Pendula: Analogy with Bubbles." In Nonlinear Systems and Complexity, 251–62. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02057-0_13.

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Conference papers on the topic "Spatio-temporal dynamical systems"

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Bandyopadhyay, P., D. Sharma, U. Konopka, and G. Morfill. "Observation of spatio-temporal pattern in magnetised rf plasmas." In INTERNATIONAL CONFERENCE ON COMPLEX PROCESSES IN PLASMAS AND NONLINEAR DYNAMICAL SYSTEMS. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4865365.

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Sharma, Balaji R., Manish Kumar, and Kelly Cohen. "Spatio-Temporal Estimation of Wildfire Growth." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-4022.

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This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deploy ability.

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Neeley, John, and John G. Harris. "Spatio-temporal simulation in subthreshold CMOS." In Applied nonlinear dynamics and stochastic systems near the millenium. AIP, 1997. http://dx.doi.org/10.1063/1.54227.

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Saha, Homagni, Tianshuang Gao, Hamid Emadi, Zhanhong Jiang, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, and Sourabh Bhattacharya. "Autonomous Mobile Sensing Platform for Spatio-Temporal Plant Phenotyping." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5207.

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This paper presents the design, modeling, control and navigation for a novel ground-based mobile sensing platform that can collect multi-modal data in agricultural research farms for high throughput modular plant phenotyping. The platform will have the following capabilities (i) Navigate in a row-crop farm to collect data with minimal human intervention during operation (ii) Autonomous decision making i.e, it can take its own decisions for maximizing the value of information of the acquired data and (iii) Scalable in terms of the size of the farmland. The design requirements for such a platform or robot is formulated, and a detailed discussion on realizing such a design is presented. The dynamics of the robot is presented in the state space form and it is abstracted in the form of a control flow diagram for the automatic steering system. An adaptive sampling approach has been taken to generate an estimated belief-space which is leveraged in the proposed opportunistic sensing scheme to generate way-points for navigation.

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Chatterjee, Nandini, and Neelima Gupte. "Quantifiers for spatio-temporal bifurcations in coupled map lattices." In Applied nonlinear dynamics and stochastic systems near the millenium. AIP, 1997. http://dx.doi.org/10.1063/1.54180.

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Xu, Yunfei, and Jongeun Choi. "Optimal Coordination of Mobile Sensor Networks Using Gaussian Processes." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2677.

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In this paper, we introduce a family of spatio-temporal Gaussian processes specified by a class of covariance functions. Nonparametric prediction based on truncated observations is proposed for mobile sensor networks with limited memory and computational power. We show that there is a trade-off between precision and efficiency when prediction based on truncated observations is used. Next, we propose both centralized and distributed navigation strategies for mobile sensor networks to move in order to reduce prediction error variances at positions of interest. Simulation results demonstrate the effectiveness of the proposed schemes.

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Aristov, V. V., and O. V. Ilyin. "Spatio-temporal Unstable Chaotic Solutions of the Carleman Kinetic System." In 27TH INTERNATIONAL SYMPOSIUM ON RAREFIED GAS DYNAMICS. AIP, 2011. http://dx.doi.org/10.1063/1.3562720.

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Andersen, Ove, and Kristian Torp. "Dynamic spatio-temporal integration of traffic accident data." In SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3274895.3274972.

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Li, Jingjing, Qiang Wang, Wenqi Zhang, Donghai Shi, and Zhiwei Qin. "Dynamic Rebalancing Dockless Bike-Sharing System based on Station Community Discovery." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/569.

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Influenced by the era of the sharing economy and mobile payment, Dockless Bike-Sharing System (Dockless BSS) is expanding in many major cities. The mobility of users constantly leads to supply and demand imbalance, which seriously affects the total profit and customer satisfaction. In this paper, we propose the Spatio-Temporal Mixed Integer Program (STMIP) with Flow-graphed Community Discovery (FCD) approach to rebalancing the system. Different from existing studies that ignore the route of trucks and adopt a centralized rebalancing, our approach considers the spatio-temporal information of trucks and discovers station communities for truck-based rebalancing. First, we propose the FCD algorithm to detect station communities. Significantly, rebalancing communities decomposes the centralized system into a distributed multi-communities system. Then, by considering the routing and velocity of trucks, we design the STMIP model with the objective of maximizing total profit, to find a repositioning policy for each station community. We design a simulator built on real-world data from DiDi Chuxing to test the algorithm performance. The extensive experimental results demonstrate that our approach outperforms in terms of service level, profit, and complexity compared with the state-of-the-art approach.

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Vorontsov, Mikhail A., and Nikita G. Iroshnikov. "Nonlinear dynamics of neuromorphic optical system with spatio-temporal interactions." In Optical Memory and Neural Networks, edited by Andrei L. Mikaelian. SPIE, 1991. http://dx.doi.org/10.1117/12.50436.

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