Academic literature on the topic 'Stochastic modelling'

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Journal articles on the topic "Stochastic modelling"

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Dobrow, Robert P. "Applied Stochastic Modelling." Technometrics 44, no. 1 (2002): 91. http://dx.doi.org/10.1198/tech.2002.s667.

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Albert, Jim. "Applied Stochastic Modelling." Journal of the American Statistical Association 97, no. 457 (2002): 354–55. http://dx.doi.org/10.1198/jasa.2002.s448.

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Auton, Tim. "Applied Stochastic Modelling." Journal of the Royal Statistical Society: Series D (The Statistician) 52, no. 2 (2003): 244. http://dx.doi.org/10.1111/1467-9884.t01-2-00356.

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Varetsky, Y., and Z. Hanzelka. "STOCHASTIC MODELLING OF A HYBRID RENEWABLE ENERGY SYSTEM." Tekhnichna Elektrodynamika 2016, no. 2 (2016): 58–62. http://dx.doi.org/10.15407/techned2016.02.058.

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Hartley, R., M. H. A. Davies, and R. B. Vintner. "Stochastic Modelling and Control." Journal of the Operational Research Society 37, no. 9 (1986): 928. http://dx.doi.org/10.2307/2582813.

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Blokker, Mirjam. "Stochastic Water Demand Modelling." Water Intelligence Online 10 (2011): 9781780400853. http://dx.doi.org/10.2166/9781780400853.

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Stemler, Thomas, Johannes P. Werner, Hartmut Benner, and Wolfram Just. "Stochastic modelling of intermittency." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1910 (2010): 273–84. http://dx.doi.org/10.1098/rsta.2009.0196.

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Recently, methods have been developed to model low-dimensional chaotic systems in terms of stochastic differential equations. We tested such methods in an electronic circuit experiment. We aimed to obtain reliable drift and diffusion coefficients even without a pronounced time-scale separation of the chaotic dynamics. By comparing the analytical solutions of the corresponding Fokker–Planck equation with experimental data, we show here that crisis-induced intermittency can be described in terms of a stochastic model which is dominated by state-space-dependent diffusion. Further on, we demonstra
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Hartley, R. "Stochastic Modelling and Control." Journal of the Operational Research Society 37, no. 9 (1986): 928–29. http://dx.doi.org/10.1057/jors.1986.158.

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Jones, P. W. "Stochastic Modelling and Analysis." Technometrics 30, no. 3 (1988): 361. http://dx.doi.org/10.1080/00401706.1988.10488425.

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Cui, Lirong, and Haitao Liao. "Stochastic modelling with applications." IMA Journal of Management Mathematics 32, no. 1 (2020): 1–2. http://dx.doi.org/10.1093/imaman/dpaa018.

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Dissertations / Theses on the topic "Stochastic modelling"

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Ozkan, Erhun. "Stochastic Inventory Modelling." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12612097/index.pdf.

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In this master thesis study, new inventory control mechanisms are developed for the repairables in Nedtrain. There is a multi-item, multi echelon system with a continuous review and one for one replenishment policy and there are different demand supply options in each control mechanism. There is an aggregate mean waiting time constraint in each local warehouse and the objective is to minimize the total system cost. The base stock levels in each warehouse are determined with an approximation method. Then different demand supply options are compared with each other.
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Baduraliya, Chaminda Hasitha. "Stochastic modelling in finance." Thesis, University of Strathclyde, 2012. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=16938.

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The trading of financial derivatives and products in financial markets has influenced the development of the world economy. Over the last few decades, a rapid growth in complex financial systems, which can generate unstable conditions in financial markets, has been observed. Therefore models are being developed to study and examine the uncertainty surrounding these financial systems in different circumstances. The important milestone of this work can be traced to the Black-Scholes formula for option pricing which was published in 1973 and revolutionized the financial industry by introducing th
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Chen, Peng. "Modelling the Stochastic Correlation." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188501.

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In this thesis, we mainly study the correlation between stocks. The correlation between stocks has been receiving increasing attention. Usually the correlation is considered to be a constant, although it is observed to be varying over time. In this thesis, we study the properties of correlations between Wiener processes and introduce a stochastic correlation model. Following the calibration methods by Zetocha, we implement the calibration for a new set of market data.<br>I det här examensarbetet fokuserar vi främst på att studera korrelation mellan aktier. Korrelationen mellan aktier har fått
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Lopes, Moreira de Veiga Maria Helena. "Modelling and forecasting stochastic volatility." Doctoral thesis, Universitat Autònoma de Barcelona, 2004. http://hdl.handle.net/10803/4046.

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El objetivo de esta tesis es modelar y predecir la volatilidad de las series financieras con modelos de volatilidad en tiempo discreto y continuo.<br/>En mi primer capítulo, intento modelar las principales características de las series financieras, como a persistencia y curtosis. Los modelos de volatilidad estocástica estimados son extensiones directas de los modelos de Gallant y Tauchen (2001), donde incluyo un elemento de retro-alimentación. Este elemento es de extrema importancia porque permite captar el hecho de que períodos de alta volatilidad están, en general, seguidos de periodos de gr
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Löfdahl, Björn. "Stochastic modelling in disability insurance." Licentiate thesis, KTH, Matematisk statistik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134233.

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This thesis consists of two papers related to the stochastic modellingof disability insurance. In the first paper, we propose a stochastic semi-Markovian framework for disability modelling in a multi-period discrete-time setting. The logistic transforms of disability inception and recovery probabilities are modelled by means of stochastic risk factors and basis functions, using counting processes and generalized linear models. The model for disability inception also takes IBNR claims into consideration. We fit various versions of the models into Swedish disability claims data. In the second pa
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Currie, James. "Stochastic modelling of TCR binding." Thesis, University of Leeds, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590430.

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A fundamental process in the immune response to infection is the activation of T cells following contact with antigen presenting cells. This activation occurs after T cell receptors on the surface of T cells bind to immunogenic peptides expressed on the surface of antigen presenting cells. The binding of T cell receptors to ligands not only leads to the activation of T cells, it is also key to T cell selection in the thymus and the maintenance of a diverse T cell receptor repertoire. T cell receptor bindings are converted into a signal which activates a T cell but there is no universal theory
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Tsang, Wai-yin, and 曾慧賢. "Aspects of modelling stochastic volatility." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31223515.

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Ferreira, Jose Antonio de Sousa Jorge. "Some contributions to stochastic modelling." Thesis, University of Sheffield, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312790.

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Luo, Yang. "Stochastic modelling in biological systems." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610145.

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Dalton, Rowan. "Modelling stochastic multi-curve basis." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27102.

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As a consequence of the 2007 financial crisis, the market has shifted towards a multi-curve approach in modelling the prevailing interest rate environment. Currently, there is a reliance on the assumption of deterministic- or constant-basis spreads. This assumption is too simplistic to describe the modern multi-curve environment and serves as the motivation for this work. A stochastic-basis framework, presented by Mercurio and Xie (2012), with one- and two-factor OIS short-rate models is reviewed and implemented in order to analyse the effect of the inclusion of stochastic-basis in the pricing
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Books on the topic "Stochastic modelling"

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Luo, Xiaoguang. GPS Stochastic Modelling. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34836-5.

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Morgan, Byron J. T. Applied stochastic modelling. 2nd ed. Chapman & Hall/CRC, 2008.

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Davis, M. H. A., and R. B. Vinter. Stochastic Modelling and Control. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4828-0.

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Germani, Alfredo, ed. Stochastic Modelling and Filtering. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/bfb0009045.

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India) International Conference on Stochastic Modelling (2002 Cochin. Advances in stochastic modelling. Edited by Artalejo J. R, Krishnamoorthy A, and International Workshop on Retrial Queues (4th : 2002 : Cochin, India). Notable Publications, 2002.

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B, Vinter R., ed. Stochastic modelling and control. Chapman and Hall, 1985.

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Wilkinson, Darren James. Stochastic modelling for systems biology. 2nd ed. Taylor & Francis, 2012.

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Christer, Anthony H., Shunji Osaki, and Lyn C. Thomas, eds. Stochastic Modelling in Innovative Manufacturing. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59105-1.

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Adler, Robert J., Peter Müller, and Boris L. Rozovskii, eds. Stochastic Modelling in Physical Oceanography. Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-2430-3.

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Hübl, Alexander. Stochastic Modelling in Production Planning. Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-19120-7.

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Book chapters on the topic "Stochastic modelling"

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Ghosh, Anindya, Bapi Saha, and Prithwiraj Mal. "Stochastic Modelling." In Textile Engineering. CRC Press, 2021. http://dx.doi.org/10.1201/9781003081234-12.

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Serovajsky, Simon. "Stochastic models." In Mathematical Modelling. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003035602-18.

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Haas, Peter J. "Modelling Power." In Stochastic Petri Nets. Springer New York, 2002. http://dx.doi.org/10.1007/0-387-21552-2_4.

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Teng, Long, Matthias Ehrhardt, and Michael Günther. "Modelling Stochastic Correlation." In Mathematics in Industry. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23413-7_14.

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Lindenschmidt, Karl-Erich. "Stochastic Modelling Framework." In River Ice Processes and Ice Flood Forecasting. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28679-8_8.

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Lindenschmidt, Karl-Erich. "Stochastic Modelling Framework." In River Ice Processes and Ice Flood Forecasting. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-49088-0_8.

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Davis, M. H. A., and R. B. Vinter. "Stochastic models." In Stochastic Modelling and Control. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4828-0_2.

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Renard, Philippe, Andres Alcolea, and David Ginsbourger. "Stochastic versus Deterministic Approaches." In Environmental Modelling. John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118351475.ch8.

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Luo, Xiaoguang. "Introduction." In GPS Stochastic Modelling. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34836-5_1.

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Luo, Xiaoguang. "Mathematical Background." In GPS Stochastic Modelling. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34836-5_2.

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Conference papers on the topic "Stochastic modelling"

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Ney, Hermann. "Stochastic modelling." In the workshop. Association for Computational Linguistics, 2001. http://dx.doi.org/10.3115/1118037.1118042.

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Garbaczewski, Piotr. "Stochastic modelling of nonlinear dynamical systems." In Stochastic and chaotic dynamics in the lakes. AIP, 2000. http://dx.doi.org/10.1063/1.1302402.

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Tautu, Petre. "Stochastic Modelling in Biology." In Proceedings of the Workshop. WORLD SCIENTIFIC, 1990. http://dx.doi.org/10.1142/9789814540711.

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Maher, Mike. "Stochastic Modelling of Sport." In 2012 Ninth International Conference on Quantitative Evaluation of Systems (QEST). IEEE, 2012. http://dx.doi.org/10.1109/qest.2012.40.

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Seddon, Keith, Behnam Pirouz, and Timothy Fitton. "Stochastic beach profile modelling." In 18th International Seminar on Paste and Thickened Tailings. Australian Centre for Geomechanics, Perth, 2015. http://dx.doi.org/10.36487/acg_rep/1504_35_seddon.

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MARIANI, L., G. TURCHETTI, and F. LUCIANI. "STOCHASTIC MODELS OF IMMUNE SYSTEM AGING." In Modelling Biomedical Signals. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812778055_0007.

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Wilczyński, Bartek. "A stochastic extension of R. Thomas regulatory network modelling." In Stochastic Models in Biological Sciences. Institute of Mathematics Polish Academy of Sciences, 2008. http://dx.doi.org/10.4064/bc80-0-19.

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CH. IVANOV, PLAMEN, and CHUNG-CHUAN LO. "STOCHASTIC APPROACHES TO MODELING OF PHYSIOLOGICAL RHYTHMS." In Modelling Biomedical Signals. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812778055_0003.

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"STOCHASTIC MODELLING IN HEALTHCARE SYSTEMS." In 1st International Conference on Simulation and Modeling Methodologies, Technologies and Applications. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003576101090115.

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Smieja, Jaroslaw. "Deterministic Modeling of Stochastic Gene Transcription Processes." In Modelling, Identification and Control. ACTAPRESS, 2014. http://dx.doi.org/10.2316/p.2014.809-018.

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Reports on the topic "Stochastic modelling"

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Yanev, Nikolay M., Vessela K. Stoimenova, and Dimitar V. Atanasov. Stochastic Modelling and Estimation of COVID-19 Population Dynamics. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2020. http://dx.doi.org/10.7546/crabs.2020.04.02.

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Ng, B. Survey of Bayesian Models for Modelling of Stochastic Temporal Processes. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/900168.

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Benoit, N., D. Marcotte, J. W. Molson, A F Bajc, and H. A. J. Russell. Stochastic hydrogeological modelling workflow in a glacial sedimentary basin, southern Ontario. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2020. http://dx.doi.org/10.4095/321107.

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Fleming, Wendell H., and Harold J. Kushner. Numerical Methods and Approximation and Modelling Problems in Stochastic Control Theory. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada218419.

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Osadetz, K. G., Z. Chen, and H. Gao. SuperSD, Version 1.0: a pool-based stochastic simulation program for modelling the spatial distribution of undiscovered petroleum resources. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2003. http://dx.doi.org/10.4095/214036.

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Ansari, S. M., E. M. Schetselaar, and J. A. Craven. Three-dimensional magnetotelluric modelling of the Lalor volcanogenic massive-sulfide deposit, Manitoba. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/328003.

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Unconstrained magnetotelluric inversion commonly produces insufficient inherent resolution to image ore-system fluid pathways that were structurally thinned during post-emplacement tectonic activity. To improve the resolution in these complex environments, we synthesized the 3-D magnetotelluric (MT) response for geologically realistic models using a finite-element-based forward-modelling tool with unstructured meshes and applied it to the Lalor volcanogenic massive-sulfide deposit in the Snow Lake mining camp, Manitoba. This new tool is based on mapping interpolated or simulated resistivity va
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Dafermos, Yannis, Andrew McConnel, Maria Nikolaidi, Servaas Storm, and Boyan Yanovski. Macroeconomic modelling in the Anthropocene: why the E-DSGE framework is not fit for purpose and what to do about it. Institute for New Economic Thinking Working Paper Series, 2024. http://dx.doi.org/10.36687/inetwp229.

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Recent years have seen an increasing use of environmental dynamic stochastic general equilibrium (E-DSGE) models for analysing the macroeconomic effects of the climate crisis. This paper explores to what extent these models are fit for purpose. We identify the limitations of the benchmark E-DSGE framework and explain how these limitations restrict the ability of this framework to meaningfully capture the macroeconomics of the climate crisis. We then explain how the assumptions behind these limitations can be relaxed, but argue that simply relaxing some of these assumptions in isolation is insu
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Perdigão, Rui A. P., and Julia Hall. Spatiotemporal Causality and Predictability Beyond Recurrence Collapse in Complex Coevolutionary Systems. Meteoceanics, 2020. http://dx.doi.org/10.46337/201111.

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Causality and Predictability of Complex Systems pose fundamental challenges even under well-defined structural stochastic-dynamic conditions where the laws of motion and system symmetries are known. However, the edifice of complexity can be profoundly transformed by structural-functional coevolution and non-recurrent elusive mechanisms changing the very same invariants of motion that had been taken for granted. This leads to recurrence collapse and memory loss, precluding the ability of traditional stochastic-dynamic and information-theoretic metrics to provide reliable information about the n
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Perdigão, Rui A. P. New Horizons of Predictability in Complex Dynamical Systems: From Fundamental Physics to Climate and Society. Meteoceanics, 2021. http://dx.doi.org/10.46337/211021.

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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 ope
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