Sentence examples for models these models from inspiring English sources

Simple-agent models: These models include representations of individual people, but represent individuals' states by a few simple variables.

However in each case of the causal allelic models, these models are directly and completely derived from precisely the hierarchical models the authors reject.

Complex-agent models: These models represent people by intelligent agents that incorporate complex "heavyweight" (Alam SJ et al. 2010) internal cognitive architectures.

To detect sentiment-aware topics, we attempt to utilize Joint Sentiment/Topic models, these models are achieved with Latent Dirichlet Allocation (LDA) based models.

The most accurate models depend on feed composition and operating parameters of the system; unlike phenomenological models, these models are difficult to implement because of their complex mathematical structure.

While the fields of tumor biology and experimental therapeutics have already benefited from ex vivo preclinical tissue models, these models have yet to address the reasons for malignant transformations and the emergence of chemoresistance.

Although general toxic or positive therapeutic effects can be investigated in vivo using suitable animal models, these model systems often do not allow to distinguish between direct effects, or indirect and bystander effects on target tissues.

Due mostly to aggregation and topological properties when modelling these models, the spatial complexity can now be also introduced [26, 47, 51].

Unlike the Bergeron model, these models also represent the total system resistance R as a distributed parameter (along with a distributed system L and C), providing a much more accurate representation of attenuation.

Like the present model, these models have mostly been deterministic, age-structured compartmental models.

Two separate authors (DWD and PJD) independently coded the model; these models gave comparable results.