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Titlebook: Computational Intelligence in Emerging Technologies for Engineering Applications; Orestes Llanes Santiago,Carlos Cruz Corona,José Lu Book

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https://doi.org/10.1007/978-3-8350-9503-8ities. We argue that how far intelligent optimization in the level designing a CPS should be viable? Thus, suitability of appropriate evolutionary and machine learning algorithms is discussed in the context of different design uncertainty of CPS. The efficacy of auto-adaptive or self-organization principle is also discussed.
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1860-949X engineering.Presents key applications, computational tools .This book explores applications of computational intelligence in key and emerging fields of engineering, especially with regard to condition monitoring and fault diagnosis, inverse problems, decision support systems and optimization. These
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Health Monitoring of Automotive Batteries in Fast-Charging Conditions Through a Fuzzy Model of the oltage term depends on a fuzzy rule-based model of the incremental capacity curve, whose linguistic expression is linked to the battery condition. The parameters of the model are learnt from samples of current and voltage obtained in charge and discharge cycles. The performance of the model is assessed in batteries with different states of health.
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,Change — Sondierungen eines Bezugsrahmens, data with lower experimental errors, and the sensitivity analysis provided a clear insight on the problem physical behavior. The results obtained confirm the good performance and effectiveness of TGO, associated with local optimization methods, in finding a good approximation to the global minimum in complex engineering problems.
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Strategie und Erfolg von FußballunternehmenCarlo method, allowing for an offline solution refinement with reduced CPU time. An application is presented considering the reconstruction of a boundary heat flux applied to a thermally thin plate. The good results obtained for this application indicate the feasibility of the proposed methodology.
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,Solution of a Coupled Conduction–Radiation Inverse Heat Transfer Problem with the Topographical Glo data with lower experimental errors, and the sensitivity analysis provided a clear insight on the problem physical behavior. The results obtained confirm the good performance and effectiveness of TGO, associated with local optimization methods, in finding a good approximation to the global minimum in complex engineering problems.
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