Sentence examples for robust predictions from inspiring English sources

"robust predictions" is grammatically correct and can be used in written English.
It is typically used to describe predictions that are reliable, strong, or able to withstand any challenges or obstacles. Here are some examples: 1. The economist's robust predictions about the stock market proved to be accurate once again. 2. The weather forecasters have made some robust predictions about a severe snowstorm hitting the East Coast. 3. Despite facing criticism, the scientist stands by his robust predictions about the effects of climate change. 4. The company's profits exceeded their initial expectations, thanks to their robust predictions about market trends. 5. The team of experts made robust predictions about the potential success of the new product, based on extensive research and data analysis.

Exact(59)

One of the most robust predictions that can be made about climate change is that it will send millions perhaps tens or hundreds of millions of people in search of new homes.

One of the most robust predictions that can be made about climate change is that it will send millions — perhaps tens or hundreds of millions — of people in search of new homes.

A bootstrap method was incorporated to estimate uncertainty and generate more robust predictions of performance.

The present Bayesian framework provides robust predictions for the behavior of granular materials using DEM simulations.

Coleman et al. (1980) developed a high-quality set of routines to calculate robust predictions for eight weight functions.

We propose to filter near-black and near-white colors during model generation to obtain more robust predictions.

Controlling these resolutions allows keeping the computational cost at a tractable level whilst still aiming at accurate and robust predictions.

The results demonstrate that the model based on the calibrated parameters is capable of offering reasonable and robust predictions.

In comparison with T1FNNs and IT2FNNs, results show that BFNNs provide more accurate and robust predictions and handle more uncertainties.

Robust predictions of charging rates and associated stochastic fluctuations are therefore required for the exposure scenarios expected throughout the mission.

This study compares the properties of evolutionary landscapes of a variety of SEMs to delineate robust predictions and possible model-specific artifacts.

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