Sentence examples for model of individual behavior from inspiring English sources

We analyse the smaller, community, scale by using a multi-species contact process coupled to a heterogeneous landscape, i.e. a stochastic spatial model of individual behavior in a system with limited resources.

As the NRC's 2012 report concludes, "These results suggest that measuring the influence of DBER and related research on teaching requires a nuanced, longitudinal model of individual behavior rather than a traditional 'cause and effect' model using a workshop or other delivery mechanism as the intervention" (p. 173).

The two main contributions of this work are the following: (1) We improve the accuracy of our previous model's assumptions of individual behavior, and thereby improve the accuracy of the model's predictions for larger rafts without sacrificing accuracy for smaller ones.

At the level of individual behavior, this model does not have the kind of justification that the exponential growth model does in the sense that the logistic equation cannot be plausibly derived from the properties of individuals.

This hierarchy of maximum entropy models allows us to dissect the role of individual behavior, pairwise relations, triplets and so on, since every model adds a unique set of independent constraints.

We apply a model of individual fisherman behavior to the red shrimp (Pleuroncodes monodon) fishery in central-southern Chile.

We integrate all the hypotheses above and create a theoretical model of individual knowledge sharing behavior in a dynamic virtual community, as seen in Fig. 1.

For example, we can use a fuzzy rule such as "IF (Temperature is High) AND (Heart Rate is High) THEN (Person is Excited)." Although fuzzy sets and operations are useful for representing the knowledge base, they fail to model the individual behavior of each and every person.

In response to this worry, theorists try to derive replicator dynamics from models of individual adaptive behavior.

The modeling of individuals' choice behavior in integrated multimodal transport networks requires the estimation of preference parameters related to the trade-off between uni-modal trips and multimodal combinations of private and public modes as well as relevant attributes of access, main and access stages of the trip.

However, while these studies aggregated data from thousands of individuals, our method focuses instead on the microscopic dynamics, modeling how individual behavior contributes to content popularity.