Sentence examples for sense to predict from inspiring English sources
It made sense to predict negative outcomes because they happened to be the most likely outcomes way back then.
Nevertheless, in spite of their methodological value, these results are not useful for a real-world application (it makes no sense to "predict" the molecular weight of a chemical compound).
Such knowledge would be useful not only in a practical sense to predict correlated changes in related traits given medical interventions to control body weight, but also from an evolutionary standpoint to elucidate the extent to which such pleiotropic modules might guide and constrain the evolution of the affected traits.
This paper demonstrates the potential of hyperspectral remote sensing to predict the chemical composition (i.e., nitrogen, phosphorous, calcium, potassium, sodium, and magnesium) of three tree species (i.e., willow, mopane and olive) and one shrub species (i.e., heather).
Further, ecological knowledge of habitat-species diversity relationships can be combined with remote sensing to predict diversity patterns over large spatial scales when sampling is logistically difficult [e.g. [66], [67]].
We used a dynamic prediction approach in the sense that to predict Hb level at a visit we used the observations of all previous visits, therefore for each visit we updated our prior information.
Apart from the strong intuitive evidence that seems to reveal beliefs and desires, we also enjoy a great deal of success when we use common sense psychology to predict the actions of other people.
However, there are limitations to using remotely sensed data to predict stand dimensions across the entire rotation.
The results of this research help quantify the role of historical yield maps and within-season remote sensing images to predict spatial patterns.
Several forms of kriging, classification and regression tree analyses have been used jointly with remotely sensed data to predict soil properties at unvisited locations aiming at obtaining continuous area coverage.
The current study introduces a new bottom up approach linking the urban Canyon Air Temperature (CAT) model with spatially distributed inputs extracted from a GIS data-base and remote sensing products to predict intra-urban temperature variability simultaneously for multiple locations in an urban environment.
