Information entropy measures applied to hierarchial complex technical and soci-technical systems
A significant increase of Systems-of-Systems (SoS) is currently observed in the social and technical domains. With increasing constituent components, Systems of Systems are becoming larger and more complex. Recent research efforts have highlighted the importance of identifying innovative statistical approaches for analyzing complex systems to better understand how they work. This research is aimed towards developing an Information Entropy based framework to analyze complex technical and social systems. Entropy in terms of information theory can be seen as the expected amount of information observed in an event. A parallel can be drawn between information entropy and system complexity, where, as a system evolves or changes its state, the information entropy will also change, thereby identifying entropy in terms of the systems components and their interactions. Towards the research goal of identifying a framework and characterizing system complexity with information entropy, work has been carried out in exploring the potential application of entropy in three different application areas to illustrate its applicability and to establish the use of information entropy within the broad horizon of complex systems. The case studies identified in the application areas used in this research help to lay a basic foundation for identifying a framework geared towards characterizing complexity and criticality, in order to analyze and assess complex systems in different operational domains.
Education|Electrical engineering|Systems science
Akundi, Satya Aditya, "Information entropy measures applied to hierarchial complex technical and soci-technical systems" (2016). ETD Collection for University of Texas, El Paso. AAI10151225.