Description
Book SynopsisThis book focuses on the definition and implementation of data-driven computational tools supporting decision-making along heterogeneous intelligence scenarios. Intelligence analysis includes methodologies, activities, and tools aimed at obtaining complex information from a set of isolated data gathered from different sensors. The tools aim at increasing the level of situation awareness of decision-makers through the construction of abstract structures supporting human operators in reasoning and making decisions. This book appeals to students, professionals, and academic researchers in computational intelligence and approximate reasoning applications. It is a comprehensive textbook on the subject, supported with case studies and practical examples in Python. The readers will learn how to define decision support systems for the intelligence analysis through the application of situation awareness and granular computing for information processing.
Table of ContentsIntroduction.- Intelligence Analysis.- Foundations of the computational techniques.- Applying Situation Awareness to Intelligence Analysis.- Decision making through what-if analysis.- System modelling with graphs.- Behaviour modelling with fuzzy signatures.- Concept drift analysis with structures of opposition.- Comparing different approaches for implementing probability based rough set operators.- Data streaming scenarios.- Dealing with continuous variables: neighborhood and dominance based rough sets.
