due to modeling error

USAGE SUMMARY

The phrase "due to modeling error" is correct and usable in written English.
It can be used to explain a problem or issue that arises as a result of inaccuracies in a model or simulation. Example: "The results of the experiment were inconclusive, primarily due to modeling error that affected the data interpretation."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

1 human-written examples

Stress uncertainty due to modeling error and the scatter in fatigue test data were considered.

Medical Engineering & Physics

Human-verified similar examples from authoritative sources

Similar Expressions

59 human-written examples

Due to modeling errors in designing ontologies, an ontology may carry incorrect information.

Expert Systems with Applications

Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations.

Communications in Nonlinear Science and Numerical Simulation

To avoid heavy computation, simplified dynamic models can be obtained by applying simplification techniques, nevertheless, performance accuracy will suffer due to modeling errors.

Mechatronics

The analytical work described includes the nominal design and its performance, the performance degradation due to modeling errors, and the performance degradation due to approximate implementation of the dynamic compensator.

Journal of Sound and Vibration

It is well known that parameter uncertainties exist inevitably in various dynamic systems due to modeling and measurement errors etc.

Advances in Difference Equations

The first two assumptions are well known in the literature of NCSs, while the last one may often arise in practical networks due to modeling or measurement errors.

Signal Processing

However, the visual tracker based on the KF, referred to as the Kalman tracker (KT), has the drawback that its performance can decrease due to modeling and computational errors.

Measurement

□ Due to modeling, computing, and measurement errors, the solution of an ill-posed equation F x) =  y, even if it exists, typically yields unacceptable results.

Applied Mathematics and Computation

Due to the modeling error of the standard LBM, the reconstructed fluxes deviate from those in the Navier Stokes equations; and to compensate this error, a complex tensor is introduced in the original MLBFS.

Journal of Computational Physics

Due to the modeling errors and some unmeasurable disturbances, it is difficult to distinguish between the effects of an actual fault and those caused by uncertainty and disturbances.

IFAC Proceedings Volumes

Expert writing Tips

Best practice

When using "due to modeling error", clearly specify which aspect of the modeling process is causing the error to enhance clarity and facilitate targeted solutions.

Common error

Avoid using "due to modeling error" as a catch-all explanation. Instead, identify specific issues such as flawed assumptions, data inaccuracies, or algorithmic limitations to provide more actionable insights.

Linguistic Context

The phrase "due to modeling error" serves as a causal explanation, indicating that inaccuracies or flaws in the modeling process are the reason for a particular outcome or problem. Ludwig AI confirms its correctness and usability.

Expression frequency: Uncommon

Frequent in

Science

50%

News & Media

25%

Formal & Business

25%

Less common in

Wiki

0%

Reference

0%

Social Media

0%

Ludwig's WRAP-UP

In summary, "due to modeling error" is a grammatically correct and usable phrase that attributes a problem or outcome to inaccuracies in a model. Ludwig AI validates its correctness. While not extremely common, it is frequently found in scientific and technical writing. It's essential to specify the source of the error within the modeling process to provide actionable insights. Consider alternatives like "because of model inaccuracies" or "resulting from simulation flaws" for variety. Avoid using it as a generic explanation without identifying the specific errors.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

because of model inaccuracies

Focuses specifically on inaccuracies within the model as the cause.

resulting from simulation flaws

Highlights flaws in the simulation process as the origin of the problem.

stemming from inaccurate models

Emphasizes that the issues originate directly from the model's lack of accuracy.

attributed to flawed modeling

Assigns the cause to the incorrect or deficient modeling techniques used.

caused by errors in the model

Directly states that errors within the model are the root cause.

due to incorrect model assumptions

Pinpoints the assumptions made in the model as the source of error.

arising from model limitations

Indicates that inherent limitations of the model lead to the problem.

on account of modeling discrepancies

Similar to "due to", but emphasizes the presence of inconsistencies in the modeling.

as a consequence of imperfect modeling

More formal way of saying "due to", pointing to the imperfect nature of the modeling.

owing to modeling inaccuracies

Replaces "due to" with "owing to", maintaining a similar level of formality and meaning.

FAQs

How can I use "due to modeling error" in a sentence?

You can use "due to modeling error" to explain why a model's predictions are inaccurate or unreliable. For example, "The discrepancy between the simulated and actual results was "due to modeling error"".

What are some alternatives to saying "due to modeling error"?

Alternatives include "because of model inaccuracies", "resulting from simulation flaws", or "caused by errors in the model". Consider the specific context to choose the most appropriate phrase.

Is it better to say "due to a modeling error" or "due to modeling error"?

Both are grammatically correct, but "due to modeling error" is generally preferred in technical writing for its conciseness and generality. Using "a" implies a single, specific error, whereas omitting it suggests a more systemic issue.

How can I minimize errors that are "due to modeling error"?

To minimize errors, validate model assumptions, use high-quality input data, refine the model iteratively based on feedback, and perform sensitivity analyses to identify key parameters influencing the results.