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Complex Webs: Anticipating the Improbable

复杂网络：预判不可能

Cambridge University Press Bruce J West Paolo Grigolini

ISBN：9780511922510，出版年：2010，中图分类号：TN

Complex Webs synthesises modern mathematical developments with a broad range of complex network applications of interest to the engineer and system scientist, presenting the common principles, algorithms, and tools governing network behaviour, dynamics, and complexity. The authors investigate multiple mathematical approaches to inverse power laws and expose the myth of normal statistics to describe natural and man-made networks. Richly illustrated throughout with real-world examples including cell phone use, accessing the Internet, failure of power grids, measures of health and disease, distribution of wealth, and many other familiar phenomena from physiology, bioengineering, biophysics, and informational and social networks, this book makes thought-provoking reading. With explanations of phenomena, diagrams, end-of-chapter problems, and worked examples, it is ideal for advanced undergraduate and graduate students in engineering and the life, social, and physical sciences. It is also a perfect introduction for researchers who are interested in this exciting new way of viewing dynamic networks.

Network complexity Worst-case complexity Implicit computational complexity Semantic complexity Fault tolerant network Accommodative infacility Generative adversarial network Parallel complexity Computability computational complexity Average-case complexity

Simplicity, Complexity and Modelling

简单、复杂性与建模

Wiley Mike Christie Andrew Cliffe

ISBN：9780470740026，出版年：2011，中图分类号：O1

Several points of disagreement exist between different modelling traditions as to whether complex models are always better than simpler models, as to how to combine results from different models and how to propagate model uncertainty into forecasts. This book represents the result of collaboration between scientists from many disciplines to show how these conflicts can be resolved. Key Features: Introduces important concepts in modelling, outlining different traditions in the use of simple and complex modelling in statistics. Provides numerous case studies on complex modelling, such as climate change, flood risk and new drug development. Concentrates on varying models, including flood risk analysis models, the petrol industry forecasts and summarizes the evolution of water distribution systems. Written by experienced statisticians and engineers in order to facilitate communication between modellers in different disciplines. Provides a glossary giving terms commonly used in different modelling traditions. This book provides a much-needed reference guide to approaching statistical modelling. Scientists involved with modelling complex systems in areas such as climate change, flood prediction and prevention, financial market modelling and systems engineering will benefit from this book. It will also be a useful source of modelling case histories.

Semantic complexity Implicit computational complexity Information-based complexity Parallel complexity Modulator complex Integral equation model Complement (complexity) Unified Model Algebraic simplification Context of computational complexity