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Descripción
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| In this chapter we propose a robust methodology for predictive modeling and optimization applied to complex systems addressing symptomatic crises. The proposed methodology is not constrained by the data availability. This system consists of a framework to generate knowledge from multi-source data. The data can be collected from multiple and heterogeneous sources with questionable reliability. From the knowledge generation, we can predict and actuate a complex system (e.g. neurological diseases) without an analytical description. In the following pages, we describe a real case study: the migraine disease. | |
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Internacional
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Si |
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DOI
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10.1002/9781119552482.ch9 |
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Edición del Libro
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Editorial del Libro
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Wiley-Vch / John Wiley & Sons, Inc. |
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ISBN
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9781119552390 |
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Serie
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Título del Libro
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Complexity Challenges in Cyber Physical Systems: Using Modeling and Simulation (M&S) to Support Intelligence, Adaptation and Autonomy |
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Desde página
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223 |
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Hasta página
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253 |