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Añadir al carritoCondición: New. Hugo Fort is a professor at the Department of Physics of the Faculty of Sciences at the University of the Republic (Montevideo, Uruguay) and the Head of the Complex Systems Group. After earning his PhD in Physics from the Autonomous University of .
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Añadir al carritoHardcover. Condición: Brand New. 336 pages. 9.18x6.12x9.21 inches. In Stock.
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Publicado por Taylor & Francis Ltd Mai 2026, 2026
ISBN 10: 1032909544 ISBN 13: 9781032909547
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Añadir al carritoBuch. Condición: Neu. Neuware - Complex systems - characterized by self-organization, emergence, and profound non-linearity - govern everything from global financial markets to ecological stability. Navigating this complexity requires a unified mathematical framework that moves beyond traditional linear models. This book provides that essential toolkit, offering a robust, interdisciplinary approach to simulation, forecasting, and management across engineering, economic, and environmental fields.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032909544 ISBN 13: 9781032909547
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Añadir al carritoHardcover. Condición: new. Hardcover. Complex systemscharacterized by self-organization, emergence, and profound non-linearitygovern everything from global financial markets to ecological stability. Navigating this complexity requires a unified mathematical framework that moves beyond traditional linear models. This book provides that essential toolkit, offering a robust, interdisciplinary approach to simulation, forecasting, and management across engineering, economic, and environmental fields.What sets this volume apart is its integration of ecological and evolutionary perspectives with quantitative approaches to simulate, forecast, and manage complexity in diverse domains including finance, agriculture, and environmental science.Throughout the book, readers will find practical examples, case studies, and advice on how to apply scientific modeling techniques to solve real-world problems. It also presents insights into best practices and strategies for using modeling and simulation effectively in various fields.This book is an indispensable resource for researchers, quantitative analysts, and advanced students in complexity science, evolutionary economics, quantitative finance, and ecological modeling. It provides the theoretical depth and practical, data-driven methods necessary to analyze and manage the world's most challenging complex systems.Key FeaturesContains an in-depth treatment of nonlinear dynamics and evolutionary processes as foundational frameworks for understanding complex system behavior.Provides applications of dynamical systems to real-world problems in ecology, environmental sciences, economics, and financial markets, emphasizing the parallels between biological evolution and market competition.Presents illustrations through a variety of case studies, featuring practical applications to S&P 500 stock dynamics, optimization of livestock production, and forecasting the collapse of threatened biomes. This book provides a unified mathematical framework to simulation, forecasting, and management across engineering, economic, and environmental fields. An essential resource for researchers, quantitative analysts, and advanced students in complexity science, evolutionary economics, quantitative finance, and ecological modeling. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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ISBN 10: 1032909544 ISBN 13: 9781032909547
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Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032909544 ISBN 13: 9781032909547
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Añadir al carritoHardcover. Condición: new. Hardcover. Complex systemscharacterized by self-organization, emergence, and profound non-linearitygovern everything from global financial markets to ecological stability. Navigating this complexity requires a unified mathematical framework that moves beyond traditional linear models. This book provides that essential toolkit, offering a robust, interdisciplinary approach to simulation, forecasting, and management across engineering, economic, and environmental fields.What sets this volume apart is its integration of ecological and evolutionary perspectives with quantitative approaches to simulate, forecast, and manage complexity in diverse domains including finance, agriculture, and environmental science.Throughout the book, readers will find practical examples, case studies, and advice on how to apply scientific modeling techniques to solve real-world problems. It also presents insights into best practices and strategies for using modeling and simulation effectively in various fields.This book is an indispensable resource for researchers, quantitative analysts, and advanced students in complexity science, evolutionary economics, quantitative finance, and ecological modeling. It provides the theoretical depth and practical, data-driven methods necessary to analyze and manage the world's most challenging complex systems.Key FeaturesContains an in-depth treatment of nonlinear dynamics and evolutionary processes as foundational frameworks for understanding complex system behavior.Provides applications of dynamical systems to real-world problems in ecology, environmental sciences, economics, and financial markets, emphasizing the parallels between biological evolution and market competition.Presents illustrations through a variety of case studies, featuring practical applications to S&P 500 stock dynamics, optimization of livestock production, and forecasting the collapse of threatened biomes. This book provides a unified mathematical framework to simulation, forecasting, and management across engineering, economic, and environmental fields. An essential resource for researchers, quantitative analysts, and advanced students in complexity science, evolutionary economics, quantitative finance, and ecological modeling. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032909544 ISBN 13: 9781032909547
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Añadir al carritoHardcover. Condición: new. Hardcover. Complex systemscharacterized by self-organization, emergence, and profound non-linearitygovern everything from global financial markets to ecological stability. Navigating this complexity requires a unified mathematical framework that moves beyond traditional linear models. This book provides that essential toolkit, offering a robust, interdisciplinary approach to simulation, forecasting, and management across engineering, economic, and environmental fields.What sets this volume apart is its integration of ecological and evolutionary perspectives with quantitative approaches to simulate, forecast, and manage complexity in diverse domains including finance, agriculture, and environmental science.Throughout the book, readers will find practical examples, case studies, and advice on how to apply scientific modeling techniques to solve real-world problems. It also presents insights into best practices and strategies for using modeling and simulation effectively in various fields.This book is an indispensable resource for researchers, quantitative analysts, and advanced students in complexity science, evolutionary economics, quantitative finance, and ecological modeling. It provides the theoretical depth and practical, data-driven methods necessary to analyze and manage the world's most challenging complex systems.Key FeaturesContains an in-depth treatment of nonlinear dynamics and evolutionary processes as foundational frameworks for understanding complex system behavior.Provides applications of dynamical systems to real-world problems in ecology, environmental sciences, economics, and financial markets, emphasizing the parallels between biological evolution and market competition.Presents illustrations through a variety of case studies, featuring practical applications to S&P 500 stock dynamics, optimization of livestock production, and forecasting the collapse of threatened biomes. This book provides a unified mathematical framework to simulation, forecasting, and management across engineering, economic, and environmental fields. An essential resource for researchers, quantitative analysts, and advanced students in complexity science, evolutionary economics, quantitative finance, and ecological modeling. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.