Of concern to the environmental modelling community is the proliferation of individual, and individualistic, models and the time associated with common model development tasks such as data transformation, coding of models, and visualisation.
The environmental modeling community has historically been concerned with the proliferation of models and the effort associated with collective model development tasks (e.g., code generation, data transformation, etc).. Environmental modeling frameworks (EMFs) have been developed to address this problem, but much work remains before EMFs are adopted as mainstream modeling tools.
Beginning with designing a functional neuroimaging study, the myriad considerations involved in the conceptual and experimental design of an informative study, from model development to task design, are discussed.
Model development is a key task in systems biology, which typically starts from an initial model candidate and, involving an iterative cycle of hypotheses-driven model modifications, leads to new experimentation and subsequent model identification steps.
Model development is a key task in systems biology, and involves different steps, such as model calibration, experimental design and model refinement which usually take place in an iterative way (see reviews in [ 1- 5]).
The major task for the model development is to couple the RANS and the LES models effectively.
Establishing guidelines for model development and dissemination is a daunting task, particularly with the complex and convoluted models used in FEA.
Although he has spent much time in model development at the CoPS, his main task is applying CGE models to policy issues.
Showing a clear assumption in a model will improve our understanding of a model's results, and will also suggest further tasks to pursue in model development.
Each task during drug designing from data preparation to model development and validation is critical to the accuracy of the predictive power of QSAR models [22].
