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Applied Decision-Making
Applications in Computer Sciences and Engineering
eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9783030179854
Veröffentl:
2019
Einband:
eBook
Seiten:
215
Autor:
Mauricio A. Sanchez
Serie:
209, Studies in Systems, Decision and Control
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions.Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.
This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions.
Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.
Evaluation of the Succession Measures of the Simultaneous Perturbation Stochastic Approximation Algorithm for the Optimization of the Process Capability Index.- An Optimization Vehicle Routing Problem approached by bio-inspired algorithms – A real case study.- Agent-based model of resistant bacterial evolution in an heterogeneous medium.- Towards intelligent systems for ubiquitous computing: tacit knowledge-inspired ubicomp.- Applied Decision Making in Design Innovation Management.- From simulation to implementation: Practical advice for policy makers who want to use computer modeling as an analysis and communication tool.- Adaptive Security based on MAPE-K: a Survey.- Interpretable Machine Learning from Granular Computing Perspective.- Nonlinear Modeling: Lessons Learned and Room for Improvement in the M&S Literature.