The United States faces numerous, varied, and evolving threats to national security, including terrorism, scarcity and disruption of food and water supplies, extreme weather events, and regional conflicts around the world. Effectively managing these threats requires intelligence that not only assesses what is happening now, but that also anticipates potential future threats. The National Geospatial-Intelligence Agency (NGA) is responsible for providing geospatial intelligence on other countriesâ€"assessing where exactly something is, what it is, and why it is importantâ€"in support of national security, disaster response, and humanitarian assistance. NGA's approach today relies heavily on imagery analysis and mapping, which provide an assessment of current and past conditions. However, augmenting that approach with a strong modeling capability would enable NGA to also anticipate and explore future outcomes. A model is a simplified representation of a real-world system that is used to extract explainable insights about the system, predict future outcomes, or explore what might happen under plausible what-if scenarios. Such models use data and/or theory to specify inputs (e.g., initial conditions, boundary conditions, and model parameters) to produce an output. From Maps to Models: Augmenting the Nation's Geospatial Intelligence Capabilities describes the types of models and analytical methods used to understand real-world systems, discusses what would be required to make these models and methods useful for geospatial intelligence, and identifies supporting research and development for NGA. This report provides examples of models that have been used to help answer the sorts of questions NGA might ask, describes how to go about a model-based investigation, and discusses models and methods that are relevant to NGA's mission.

In this book authors for the first time introduce new mathematical models analogous to Fuzzy Cognitive Maps (FCMs) and Neutrosophic Cognitive Maps (NCMs) models. Several types of MOD Cognitive Maps models are constructed in this book. They are MOD Cognitive Maps model, MOD dual number Cognitive Maps model, MOD neutrosophic Cognitive Maps model, MOD finite complex number Cognitive Maps model, MOD special dual like number Cognitive Maps model, and MOD special quasi dual number Cognitive Maps model.

In this book the authors for the first time construct MOD Relational Maps model analogous to Fuzzy Relational Maps (FRMs) model or Neutrosophic Relational Maps (NRMs) model using the MOD rectangular or relational matrix. The advantage of using these models is that the MOD fixed point pair or MOD limit cycle pair is obtained after a finite number of iterations.

In this paper for the first time two new fuzzy models viz Merged Fuzzy Cognitive Maps (MFCMs) models and Specially Merged Linked Fuzzy Cognitive Maps (SMLFCMs) are introduced. To compare the experts opinion a new techniques called Kosko Hamming distance and Kosko Hamming weight are introduced.

The 5th Experimental Chaos Conference was a gathering of scientists and engineers who work on real-world systems that behave in a nonlinear and, often, chaotic fashion. The proceedings present discoveries of chaotic behavior, explanation of nonlinear phenomena in the laboratory, and applications of nonlinear and chaotic effects to devices and techniques for improving performance and surmounting technical obstacles. Experimental work is presented on chaos in semiconductor superlattices, spatiotemporal chaos in magnetic materials, instabilities in magnetic fluids, bifurcations of hexagonal patterns in lasers, and discrete rotating waves. New phenomena are exhibited on amplitude death in coupled oscillators, vortex crystals, wakes in soap films, chaotic dynamics of ocean waves, and microscopic chaos. Applications of chaotic dynamics are offered in the areas of chaotic pulse trains in digital communications, detection of changes in EEGs, detection of unstable periodic orbits in noisy data, cellular automata and warfare, detection of n: m phase synchronization, methods in acoustic chaos, chaos in the machine tool-cutting process, and a nonlinear airfoil. The broad range of topics and fields touches on a wide variety of systems whose behavior is now better understood and applied through the use of chaotic dynamics