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The prediction of behavior of complex systems, analysis and modeling of its structure is a vitally important problem in engineering, economy and generally in science today. Examples of such systems can be seen in the world around us (including our bodies) and of course in almost every scientific discipline including such “exotic” domains as the earth’s atmosphere, turbulent fluids, economics (exchange rate and stock markets), population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such complex dynamics, which often exhibit strange behavior, and to use it in research or industrial applications, i...
Prediction of behavior of the dynamical systems, analysis and modeling of its structure is vitally important problem in engineering, economy and science today. Examples of such systems can be seen in the world around us and of course in almost every scientific discipline including such “exotic” domains like the earth’s atmosphere, turbulent fluids, economies (exchange rate and stock markets), population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such dynamics and to use it in research or industrial applications, it is important to create its models. For this purpose there is rich spectra of me...
Evolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive resear...
This volume contains papers presented at the 2nd International Afro-European Conference for Industrial Advancement -- AECIA 2015. The conference aimed at bringing together the foremost experts and excellent young researchers from Africa, Europe and the rest of the world to disseminate the latest results from various fields of engineering, information, and communication technologies. The topics, discussed at the conference, covered a broad range of domains spanning from ICT and engineering to prediction, modeling, and analysis of complex systems. The 2015 edition of AECIA featured a distinguished special track on prediction, modeling and analysis of complex systems -- Nostradamus, and special sessions on Advances in Image Processing and Colorization and Data Processing, Protocols, and Applications in Wireless Sensor Networks.
This book is a collection of selected accepted papers of Mendel conference that has been held in Brno, Czech Republic in June 2015. The book contents three chapters which represent recent advances in soft computing including intelligent image processing and bio-inspired robotics.: Chapter 1: Evolutionary Computing, and Swarm intelligence, Chapter 2: Neural Networks, Self-organization, and Machine Learning, and Chapter3: Intelligent Image Processing, and Bio-inspired Robotics. The Mendel conference was established in 1995, and it carries the name of the scientist and Augustinian priest Gregor J. Mendel who discovered the famous Laws of Heredity. In 2015 we are commemorating 150 years since Mendel's lectures, which he presented in Brno on February and March 1865. The main aim of the conference was to create a periodical possibility for students, academics and researchers to exchange their ideas and novel research methods.
This is the first book devoted entirely to Differential Evolution (DE) for global permutative-based combinatorial optimization. Since its original development, DE has mainly been applied to solving problems characterized by continuous parameters. This means that only a subset of real-world problems could be solved by the original, classical DE algorithm. This book presents in detail the various permutative-based combinatorial DE formulations by their initiators in an easy-to-follow manner, through extensive illustrations and computer code. It is a valuable resource for professionals and students interested in DE in order to have full potentials of DE at their disposal as a proven optimizer. All source programs in C and Mathematica programming languages are downloadable from the website of Springer.