Sentence examples for model improvement and from inspiring English sources

It will then discuss how such techniques can be incorporated into strategies for model improvement and will try to provide some future perspectives on how we can proceed in this direction as a research community.

There, the objective is towards assessing errors in numerical models of air quality and utilizing concentration measurements from monitors to provide the bases for guidance towards model improvement and for their assessment of ability to predict and retrospectively map air quality.

The goal is model improvement and the ability to measure gravity theory signals closer to the inherent noise limits of the data, being in this case a factor 4 or 5 smaller than the present 'realistic uncertainties' allowed for incomplete modeling.

Therefore, in this study, efforts are being made to study the impacts of solar activity on the prediction of the latest IRI-2012 model simultaneously as low, EIA to mid latitudes during ascending phase of solar activity from 2009 to 2013 which might be useful for the IRI model improvement and the model error representation of the data assimilation.

Our results comparing the IRI-2012 TEC with ground-based GPS measurements simultaneously from low- to mid-latitude regions during long period (2009 to 2013) might be useful for the IRI model improvement and the model error representation of the data assimilation.

Repeated fly surveillance in these areas would aid both in model improvement and in possible early detection of fly belt expansion.

The needs for model improvements and further calibration are finally discussed.

Improvements to the current models are part of a continuing process and the recent model improvements and future possibilities in lunar gravity modeling are discussed.

With model improvements and increased expert use of the tool, we estimate that profit gains over current grower practices can be expected in at least four out of five cases.

Along with the deeper understanding of biogeophysical and biogeochemical processes, the software complexity of those earth system models becomes a barrier for further rapid model improvements and validation.

Previous curiosity-based agents acquired skills by associating intrinsic rewards with world model improvements, and used reinforcement learning to learn how to get these intrinsic rewards.