1st Edition

Handbook of Applications of Chaos Theory

Edited By Christos H. Skiadas, Charilaos Skiadas Copyright 2016
948 Pages
by Chapman & Hall

952 Pages 612 B/W Illustrations
by Chapman & Hall

952 Pages 612 B/W Illustrations
by Chapman & Hall

In addition to explaining and modeling unexplored phenomena in nature and society, chaos uses vital parts of nonlinear dynamical systems theory and established chaotic theory to open new frontiers and fields of study. Handbook of Applications of Chaos Theory covers the main parts of chaos theory along with various applications to diverse areas. Expert contributors from around the world show how... Read more

Chaos and Nonlinear Dynamics. Strange Attractors, Bifurcation, and Related Theory. Chaotic Data Analysis, Equations, and Applications. Chaos in Plasma. Chaos in Flows and Turbulence. Chaos and Quantum Theory. Optics and Chaos. Chaos Theory in Biology and Medicine. Chaos in Mechanical Sciences. Chaotic Pattern Recognition. Chaos in Socioeconomic and Human Sciences. Chaos in Music. Index.

Biography

Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete. He is chair of the Chaotic Modeling and Simulation Conference series. He has published more than 80 papers, three monographs, and 12 books, including Chaotic Modeling and Simulation: Analysis of Chaotic Models, Attractors and Forms (Chapman & Hall/CRC, October 2008). His research interests include innovation diffusion modeling and forecasting, life table data modeling, healthy life expectancy estimates, and deterministic, stochastic, and chaotic modeling.



Charilaos Skiadas, PhD, is an associate professor in mathematics and computer science at Hanover College. He is the coauthor of Chaotic Modeling and Simulation: Analysis of Chaotic Models, Attractors and Forms (Chapman & Hall/CRC, October 2008). His research interests encompass a wide array of mathematical and computing topics, ranging from algebraic geometry to statistics and programming languages to data science.