About the Journal

International Journal of Network Dynamics and Intelligence (IJNDI) serves as a uniquely positioned world-leading journal dedicated to publishing high quality, rigorously reviewed, original papers that contribute to the methodology and practice in the field of network dynamics and network intelligence, where theory, practice and applications are the essential topics being covered.

People may not appreciate it but networks do exist in our lives. The brain is a complex network. The global economy is a network of national economies. Computer viruses routinely spread through the Internet. Food-webs, ecosystems, and metabolic pathways can be represented by networks. Energy is distributed through transportation networks in living organisms, man-made infrastructures, and other physical systems.

The complexity of networks in the social, biological, engineering and physical sciences gives rise to many challenges for scientists and engineers, which have been overlooked by the traditional disciplines. For example, how to better understand and utilize network dynamics to assure secure communication in case of possible loss or leak of information in the network communication? How do cascading failures propagate throughout a large power transmission grid or a global financial network? What is the most efficient and robust architecture for an organization or an artefact in an uncertain environment? How to analyse and control synchronization behaviour in complex networks? How to understand, model and utilise group intelligence that emerges from the networked collaboration, collective efforts, and competition of many individuals for consensus decision making?

In response to the challenges identified above, there has been an ever-growing demand for better understanding network dynamics and network intelligence. As such, IJNDI has been launched to provide an ideal platform for control engineers, mathematicians, and computer scientists to manage, analyse, interpret and synthesize functional information on dynamics and intelligence arising from various networks that include general networks, neural networks, emerging networks, network intelligence, network learning, network optimization, as well as interdisciplinary topics with artificial intelligence, cognitive science, computational learning theory, fuzzy logic, evolutionary algorithms, information theory, machine learning, neurobiology and pattern recognition.