Sentence examples for methodology in modeling from inspiring English sources

Following this review, the authors describe the technical details of their methodology in modeling the positional uncertainty of geospatial utility data, monitoring the excavator movement, and synergizing them into a geospatial AR environment for real-time visualization and proximity analysis.

In this paper, basic concepts about fractional calculus and fractional rheology used in the study of viscoelastic behavior of materials and the application of this methodology in modeling the creep phenomenon are presented; also the solution of a differential equation fractional modeling this phenomenon is commented.

In this study, we developed a simple non-linear regression methodology in modeling and forecasting malaria incidence in Chennai city, India, and predicted future disease incidence with high confidence level.

Weaknesses have been identified with this methodology in modeling disease progression, obtaining good quality information on costs for patients treated in the community, and sensitivity to small changes in estimated incremental costs.

Shewchuk et al. (2017) provided a methodology in modeling and assessing the complex multi-worker physical processes which helped establish the ergonomic implications of the operations.

A novel methodology in modelling repeated ball impacts was established and proven.

As lignocellulosic biomass is more complex in structure compared to synthetic polymers, the challenges and methodology involved in modeling the degradation of its basic constituents, viz.

However, the traditional GO methodology is insufficient in modeling the system with feedback signals, which are common in those systems.

However, these disadvantages do not seem to impose serious limitations because the modeling approach presented here can be potentially extended to more general delivery/collection geometries as well as multilayer tissue geometries by following a similar methodology in model development.

This can be easily achieved, by a plethora of gene knockouts (KOs) methodologies in model systems ranging from E. coli to mice.

Although this causes loss of information [ 25], these procedures were retained since they are part of the frequently used standard statistical methodology in predictive modeling.