Potential applications, not yet fully explored, include ability to automatically connect models and data sources, using the ontology to organize model bases containing many models and model components, and using ontology reasoners to search for models, automatically discover model similarities and differences, and generate model instances from general principles.
Finally, we present an extensive experimental study for different graph classes and model instances.
We do not see any problem with that because we consider our model instances as an internal and intermediary representations, that is, it can be discarded or ignored as long as they had been used.
Just as crucial as comparing population averages with simulation averages and comparing single-cell data sets to sets of single model instances, accurate pairing of measured and modeled entities is key to the development of high-quality models.
A comprehensive seismic risk analysis of this region is conducted, with over 300 random variables, 30 model types, and 4000 model instances.
In this figure, the average overlap O vs. the maxRAF size is plotted for 20 model instances with p x, r)=0.00041 and 20 instances with p x, r)=0.00045 (40 points in total).
There are mainly three types of data model instances, i.e. conceptual, logical and physical [103].
By allowing fast evaluation of predicates such as 'can-see'under',r', and 'inside', these model instances support coherent text interpretation.
In the experiments, five methods of scraping queries from modification requests and seven retrieval model instances are considered.
Taking 20 model instances that contain an RAF set, and with irrRAF samples of size S=10,000, all irrRAFs within each sample turn out to be different for all of these 20 instances.
