Long-Time Predictions in Dynamics PDF Download

Author: V.G. Szebehely
Publisher: Springer Science & Business Media
ISBN: 9401014930
Category : Science
Languages : en
Pages : 363

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Proceedings of the NATO Advanced Study Institute, Cortina D'Ampezzo, Italy, August 3-16, 1975

Author: Stephen J. Taylor
Publisher: Princeton University Press
ISBN: 1400839254
Category : Business & Economics
Languages : en
Pages : 544

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Book Description
This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.

Author: Board on Atmospheric Sciences and Climate
Publisher: National Academies Press
ISBN: 0309517656
Category : Science
Languages : en
Pages : 424

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Book Description
Technology has propelled the atmospheric sciences from a fledgling discipline to a global enterprise. Findings in this field shape a broad spectrum of decisions--what to wear outdoors, whether aircraft should fly, how to deal with the issue of climate change, and more. This book presents a comprehensive assessment of the atmospheric sciences and offers a vision for the future and a range of recommendations for federal authorities, the scientific community, and education administrators. How does atmospheric science contribute to national well-being? In the context of this question, the panel identifies imperatives in scientific observation, recommends directions for modeling and forecasting research, and examines management issues, including the growing problem of weather data availability. Five subdisciplines--physics, chemistry, dynamics and weather forecasting, upper atmosphere and near-earth space physics, climate and climate change--and their status as the science enters the twenty-first century are examined in detail, including recommendations for research. This readable book will be of interest to public-sector policy framers and private-sector decisionmakers as well as researchers, educators, and students in the atmospheric sciences.

Author: Sergio Consoli
Publisher: Springer Nature
ISBN: 3030668916
Category : Application software
Languages : en
Pages : 357

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Book Description
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Author: Matteo Sangiorgio
Publisher: Springer Nature
ISBN: 3030944824
Category : Mathematics
Languages : en
Pages : 111

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Book Description
The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. This is relevant for many applications, such as model predictive control, that requires predicting the values for the whole receding horizon. Going progressively from deterministic models with different degrees of complexity and chaoticity to noisy systems and then to real-world cases, the book compares the performances of various neural network architectures (feed-forward and recurrent). It also introduces an innovative and powerful approach for training recurrent structures specific for sequence-to-sequence tasks. The book also presents one of the first attempts in the context of environmental time series forecasting of applying transfer-learning techniques such as domain adaptation.

Author: Igor Nesteruk
Publisher: Springer Nature
ISBN: 9813364165
Category : Science
Languages : en
Pages : 172

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Book Description
This book highlights the estimate of epidemic characteristics for different countries/regions in the world with the use of known SIR (susceptible-infected-removed) model for the dynamics of the epidemic, the known exact solution of the linear differential equations and statistical approach developed before. The COVID-19 pandemic is of great interest to researchers due to its high mortality and a negative impact to the world economy. Correct simulation of the pandemic dynamics needs complicated mathematical models and many efforts for unknown parameters identification. The simple method of detection of the new pandemic wave is proposed and SIR model generalized. The hidden periods, epidemic durations, final numbers of cases, the effective reproduction numbers and probabilities of meeting an infected person are presented for countries like USA, Germany, UK, the Republic of Korea, Italy, Spain, France, the Republic of Moldova, Ukraine, and for the world. The presented information is useful to regulate the quarantine activities and to predict the medical and economic consequences of different/future pandemics.

Author: C. A. Brebbia
Publisher: WIT Press
ISBN: 1845646541
Category : Nature
Languages : en
Pages : 369

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Book Description
This book contains a series of outstanding contributions on ecodynamics that appeared in limited editions before the emergence of the International Journal of Design & Nature and Ecodynamics, which has now become the primary focus for this area of research.The aim of ecodynamics is to relate ecosystems to evolutionary thermodynamics, which can lead to appropriate solutions for sustainable development. The contributions published in this volume relate to all aspects of ecosystems and sustainable development, ranging from physical sciences to economics and epistemology.The world of ecosystems has been dominated by the towering personality of Ilya Prigogine to whom this volume is dedicated. The first article is an extract from his autobiography written shortly before he died.Prigogine's ideas are directly reflected in many of the contributions in this volume. He helped set up numerous research groups all around the world, including that at Siena University headed by the late Enzo Tiezzi. He also influenced the work of Sven Jorgensen, Bernard Patten, Robert Ulanowicz, Simone Bastianoni, Nadia Marchettini, Ricardo Pulselli, T-S Chon, to name just a few amongst the many authors contributing to this volume.This compilation of influential papers currently unavailable in the open literature will make an important contribution to the field of ecodynamics.

Author: Peter Turchin
Publisher: Princeton University Press
ISBN: 1400889316
Category : History
Languages : en
Pages : 260

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Book Description
Many historical processes are dynamic. Populations grow and decline. Empires expand and collapse. Religions spread and wither. Natural scientists have made great strides in understanding dynamical processes in the physical and biological worlds using a synthetic approach that combines mathematical modeling with statistical analyses. Taking up the problem of territorial dynamics--why some polities at certain times expand and at other times contract--this book shows that a similar research program can advance our understanding of dynamical processes in history. Peter Turchin develops hypotheses from a wide range of social, political, economic, and demographic factors: geopolitics, factors affecting collective solidarity, dynamics of ethnic assimilation/religious conversion, and the interaction between population dynamics and sociopolitical stability. He then translates these into a spectrum of mathematical models, investigates the dynamics predicted by the models, and contrasts model predictions with empirical patterns. Turchin's highly instructive empirical tests demonstrate that certain models predict empirical patterns with a very high degree of accuracy. For instance, one model accounts for the recurrent waves of state breakdown in medieval and early modern Europe. And historical data confirm that ethno-nationalist solidarity produces an aggressively expansive state under certain conditions (such as in locations where imperial frontiers coincide with religious divides). The strength of Turchin's results suggests that the synthetic approach he advocates can significantly improve our understanding of historical dynamics.

Author: Andreas S. Weigend
Publisher: Routledge
ISBN: 042997227X
Category : Social Science
Languages : en
Pages : 665

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Book Description
The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques that are used to study time series, both as a reference for experts and as a guide for novices.

Author: Susan Friedlander
Publisher: Gulf Professional Publishing
ISBN: 9780444512871
Category : Mathematics
Languages : en
Pages : 640

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Book Description
Cover -- Contents of the Handbook: Volume 1 -- Content -- Preface -- List of Contributors -- Chapter 1. Statistical Hydrodynamics -- Chapter 2. Topics on Hydrodynamics and Volume Preserving Maps -- Chapter 3. Weak Solutions of Incompressible Euler Equations -- Chapter 4. Near Identity Transformations for the Navier-Stokes Equations -- Chapter 5. Planar Navier-Stokes Equations: Vorticity Approach -- Chapter 6. Attractors of Navier-Stokes Equations -- Chapter 7. Stability and Instability in Viscous Fluids -- Chapter 8. Localized Instabilities in Fluids -- Chapter 9. Dynamo Theory -- Chapter 10. Water-Waves as a Spatial Dynamical System -- Chapter 11. Solving the Einstein Equations by Lipschitz Continuous Metrics: Shock Waves in General Relativity -- Author Index -- Subject Index