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Titlebook: Applications of Evolutionary Computation; EvoApplications 2012 Cecilia Chio,Alexandros Agapitos,Georgios N. Yanna Conference proceedings 20

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Actor-Network-Theory and Creativity Research. For this purpose, we have used two multi-objective evolutionary algorithms: NSGA-II and SPEA-2. We have done experiments over various sceneries, checking by means of statically techniques that SPEA-2 offers better results for more complex instances.
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Actor-Network-Theory and Creativity Researchmodifies its next set of sequences accordingly. Such an exploration results in a set of command sequences that reflect correct uses of the service in testing. These discovered sequences can then be used to identify the service, unforeseen uses of the service, and, most importantly, potential weaknesses.
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Actor-Network-Theory and Creativity Research-II (NSGA-II) to evaluate the multi-objective properties and prove its reliability. Moreover, MOSWO has been compared with real schedulers, the Workload Management System (WMS) from gLite and the Deadline Budget Constraint (DBC) from Nimrod-G, improving their results.
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Actor-Network-Theory and Creativity Researchtatistical time-series modelling. Empirical results suggest that GP is able to successfully induce seasonal forecasting models, and that autoregressive models compose a more stable unit of evolution in terms of generalisation performance for the three datasets investigated.
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