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We use a combination of exploratory and data mining techniques to understand data generated from an existing agent-based model to understand the model’s behavior and its sensitivity to initial configurations of its parameters.This is a step in the direction of an ongoing research in the social simulation community to incorporate more sophisticated techniques to better understand how different parameters and internal processes influence outcomes of agent-based models.The authors suggested different data mining techniques such as regression, cluster analysis, analysis of variance (ANOVA), and association rules for this purpose.For illustration, Remondino and Correndo () presented a case study in which a biological phenomenon involving some species of cicadas was analyzed by performing multiple runs of simulations and aggregating the results. () proposed a methodological approach involving a data mining step to validate and improve the results of an agent-based model.In every way ;-)But by far not just any man out there; You got to be special...Leeftijd 39 Uit: Stalybridge, United Kingdom - Online Nu Crossdresser Zoekt Man (483 km afstand) A quite and sometimes shy person at first though once i get to know and trust someone, i can get quite wild and submissive.However, the number of parameters and agents’ rules of interaction grows rapidly.Such models often have unvalidated parameters that must be introduced by the modeler in order for the model to be fully functional.
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The next section (“Agent-based models tend to generate large volumes of simulated data that is dynamic and high-dimensional, making them (sometimes extremely) difficult to analyze.
Various exploratory data analysis (EDA) and data mining (DM) techniques have been reported to explore and understand a model’s outcome against different input configurations (e.g., Villa-Vialaneix et al. These techniques include heat-maps, box and whisker plots, sensitivity, classification trees, the K-means clustering algorithm and ranking of model parameters’ in influencing the model’s outcomes.
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