Mathematical Topics on Modelling Complex Systems

This book explores recent developments in theoretical research and mathematical modelling of real-world complex systems, organized in four parts.

This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.

Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights.

This book includes the proceedings of the 19th International Scientific Conference “Energy Management of Municipal Transportation Facilities and Transport EMMFT 2017”, which was held in Khabarovsk, Russia on 10–13 April 2017. The book presents the research findings of scientists working at universities in the Far Eastern, Siberian and Ural Federal Districts of Russia, and of Serbia, which are unique regions notable for sustainably operating complex transport infrastructures in severe climatic and geographic environments. It also offers practical insights into transportation operation under such conditions.