Sentence examples for increasing the predictability from inspiring English sources

But increasing the predictability for the college is precisely what reduces the predictability for the applicant.

We intend to combine the bigram and the PLSA models to take advantage of the strengths of both models for increasing the predictability of words in documents.

Public transit systems like the MBTA work best when they limit congestion by taking cars off the road, and thus reducing delays, travel time and increasing the predictability of a commute.

The still existing high drug failure rate in clinical trials calls for novel cell culture devices increasing the predictability of ADME/Tox assays as well as short- and long-term in vitro safety testing of potential drug compounds.

Doing this, as well as adopting the rules and regulations associated with the technology, helps to lower the transaction costs of monitoring other industries' actions, in effect, increasing the predictability of their strategies; but this also facilitates policy planning, while leveling competition and assuring profits.

Both schemes seek to increase the predictability and efficiency of tort law outcomes, but they have little else in common.

Recent advances in the nascent field of synthetic biology have increased the predictability of small-molecule production in engineered cells growing under constant conditions.

To increase the predictability and reliability of this approach it is necessary to understand the mechanisms underlying herbivore population response to diversified agro-ecosystems.

First, the data highlight that designing products under variable use conditions enabled firms to optimize products for widespread use and to increase the predictability of product outcomes.

Thus, refocusing harmful algal bloom management by integrating ecological and phylogenetic factors acting on toxin and bioactive peptide synthesis gene distribution and concentrations could increase the predictability of the risks originating from Planktothrix blooms.

To increase the predictability of the process, intelligent models have been developed based on back-propagation neural network (BPNN) and accuracy of these models was compared with mathematical models based on root mean square error (RMSE) and prediction error percent (PEP).