Titlebook: Computational Intelligence; Collaboration, Fusio Christine L. Mumford,Lakhmi C. Jain Book 2009 Springer-Verlag Berlin Heidelberg 2009 Multi

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The Analysis of Crowd Dynamics: From Observations to Modellingdes computer vision has become increasingly interested in studying crowds and their dynamics: because the phenomenon is of great scientific interest, it offers new computational challenges and because of a rapid increase in video surveillance technology deployed in public and private spaces. In this

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Michiel Hazewinkel,Jan C. Willemscomplexity tradeoff surface in some studies. These studies are often referred to as multiobjective genetic fuzzy systems. In this chapter, we first briefly explain the concept of accuracy-complexity tradeoff in the design of fuzzy rule-based systems. Next we explain various studies in multiobjective

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M. H. A. Davis,Steven I. Marcusing is the most widely used methodology. A detailed discussion is presented including the steps needed to apply this technique, some representative case studies, a literature review of related work, and a discussion of relevant issues. Our aim is to convey the exciting potential of this innovative a

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https://doi.org/10.1007/978-3-031-54071-4onomous collaborations is sensed and monitored by a central unit. The collaboration complexity, which is the collective problem solving capability of the design system, is compared to the complexity of the problem estimated from simulation based techniques. In this regard IMMUNE is an artificial imm

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Arthur C. Heinricher,Richard H. Stockbridgeds employing ensembles are as capable as most individual human beings are in their ability to predict the social impressions certain faces make on the average human observer. Single classifier systems did not match human performance as well as the ensembles did. Included in this chapter is a tutoria

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