This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the
This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theor
This volume sheds light on the current state of complex networks and nonlinear dynamics applied to the understanding of economic and social phenomena ranging from geographical economics to macroeco
??This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution, the methodologies and t
This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined
The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the boo
This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors’ new findings on determining the optimal so
Understanding the dynamics of multi-phase flows has been a challenge in the fields of nonlinear dynamics and fluid mechanics. This chapter reviews our work on two-phase flow dynamics in combination wi
In this book for the first time two scientific fields - consensus formation and synchronization of communications - are presented together and examined through their interrelational aspects, of rapidl
Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In th
For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized
Written from the physicist’s perspective, this book introduces computational neuroscience with in-depth contributions by system neuroscientists. The authors set forth a conceptual model for complex ne
The customer base is an important value driver of software companies and a reliable prediction of its development is fundamental for investment decisions. A particularity in software markets is that a
We live in a networked world. People are getting more and more interconnected through the new information and communication technologies, like mobile phones and the Internet.The function of cells can
A state-of-the-art survey that reports on the progress made in selected areas of this important and growing field, aiding the analysis of existing networks and the design of new and more efficient alg
This book introduces methods of robust optimization in multivariate adaptive regression splines (MARS) and Conic MARS in order to handle uncertainty and non-linearity. The proposed techniques are impl
This book gives a concise overview of the mathematical foundations of kinetics used in chemistry and systems biology. The analytical and numerical methods used to solve complex rate equations with the
This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls a
This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes a
This book offers a unified approach to complex practical problems in Earth Sciences, showing how neural networks are well suited for applications in satellite remote sensing, meteorology, hydrology, o
Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated wit
The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine h
Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the
With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown tha
How can our societies be stabilized in a crisis? Why can we enjoy and understand Shakespeare? Why are fruitflies uniform? How do omnivorous eating habits aid our survival? What makes the Mona Lisa’s s
Information and Control in Networks demonstrates the way in which system dynamics and information flows intertwine as they evolve, and the central role played by information in the control of complex
Signaling networks are composed of numerous signaling pathways and each has its own intricate component parts. Signaling outputs are dynamic, extraordinarily complex and yet highly specific. In, Comp
The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory;
From the beginning of the OMICs biology era, science has been pursuing the reduction of the complex "genome-wide" assays in order to understand the essential biology that lies beneath it. In Protein N
From the beginning of the OMICs biology era, science has been pursuing the reduction of the complex "genome-wide" assays in order to understand the essential biology that lies beneath it. In Protein N
This utterly comprehensive work is thought to be the first to integrate the literature on the physics of the failure of complex systems such as hospitals, banks and transport networks. It has chapters
WINNER OF THE 2001 DEGROOT PRIZE!Probabilistic expert systems are graphical networks that support the modelling of uncertainty and decisions in large complex domains, while retaining ease of calculat
Dynamical models on graphs or random graphs are increasingly used in applied sciences as mathematical tools to study complex systems whose exact structure is too complicated to be known in detail. Bes
This book covers the latest techniques for analysing and representing the complex, multi-layered data now available to geographers studying urban zones and their populations, from network analysis too
This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic as
Optical networks epitomize complex communication systems, and they comprise the Internet’s infrastructural backbone. The first of its kind, this book develops the mathematical framework needed from a
This work addresses time-delay in complex nonlinear systems and, in particular, its applications in complex networks; its role in control theory and nonlinear optics are also investigated. Delays aris
By the end of the 1970s, contaminated sites had emerged as one of the most complex and urgent environmental issues affecting industrialized countries. The authors show that small and prosperous Switze
A persistent problem when finding communities in large complex networks is the so-called resolution limit. This thesis addresses this issue meticulously, and introduces the important notion of resolut
The auditory system is a complex neural system composed of many types of neurons connected into networks. One feature that sets the auditory system apart from other sensory systems, such as somatosens
