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This model enhances the VCV model because of complementing some determining factors.
The presented model enhances the MEDALUS methodology developed by European Commission.
The model enhances the capability of the adapted TsHARP in unmixing temperature with decreasing resolution.
Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model.
Compared with results of the Hu and Wang model, proposed model enhances the separation results about 1.48 dB for overall mean.
Therefore, when integrated with the pre-existing symbolic knowledge model, the ANN model enhances the decision-making ability of the intelligent system for tribological design of engines.
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Authors stated that the proposed model enhanced the controlling and reasoning capacity of BDI model.
Including habit strength in the TPB model enhanced the explained variance of speeding intention by 26.7%.
The IAMF model enhanced the recognition accuracy by 19% over AMF and by 42.86% over AM for metal recognition.
Using rubber scrapers in DSSSHS model enhanced the total internal heat transfer coefficient (h1) as well as the productivity.
Results indicated that CM model enhanced the accuracy of final prediction and performed more satisfyingly compared with individual model acting alone.
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