Sentence examples for model error detection from inspiring English sources

For future work, the authors are exploring other applications to be integrated in the proposed system, such as LSE-based real-time contingency analysis, dynamic phase angle for overloading, real-time model error detection, and transmission equipment health monitoring.

In this way, here we present a Bayesian-network-based model that allows error detection and prediction in high-precision foundries.

A fuzzy reasoning and verification Petri nets (FRVPNs) model is established for an error detection and diagnosis mechanism applied to a complex fault-tolerant PC-controlled system.

These reports support scientific writing because sophisticated formulas can be directly adopted and ease the error detection and model communication.

Furthermore, as long as and are set to 0, our scheme achieves a simple switch from the joint compression, error detection, and encryption model to a standard compression model.

This clustering or bias more likely stems from model errors than from detection errors and could at least partially explain the large gap between theoretical bound and RMSE in Table 4. Working with three-dimensional data in the plane is of course another model discrepancy that could have greater impact than we first anticipated.

For a broader understanding of the models, support in scientific writing and error detection, a human-readable report of the complete model is needed.

The design of models of a circuit for error detection and correction that is used between the microprocessor and memory fulfil the error-control function, which performs flow-through error detection and correction of data written to, and read from the memory.

Advances in modeling including optimization, product modeling, fault detection and diagnostics, inverse models.

We firstly study a wireless router system model with a sequential convolutional decoder for error detection and correction in order to investigate QoD of flow and error control.

We introduced a new statistic for error detection that uses a hierarchical model for the stepwise process of first selecting a subset of reads from a genome and then introducing errors during sequencing.