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Neither LSTMs nor sentiment analysis are new, but combining them in a way that reportedly breaks records for sentiment analysis accuracy on commonly used benchmarking data sets is worth note — particularly when you account for the efficiency of the models.
However, the ability to do so is constrained by the efficiency of the models used during the process.
Also, a comprehensive assessment was provided about the feasibility and efficiency of the models along with an evaluation of the hysteresis between bounding drainage and imbibition curves.
First, there are still many unmeasurable or uncontrollable factors in their models, such as institutional, cultural, social, and geographical factors, which may reduce the efficiency of the models.
To evaluate the efficiency of the models for simulating monthly river flow data are divided into two groups, each used separately in the training and testing periods.
The aim is to find the minimum value of total cost by varying different parameters and compare the efficiency of the models.
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The robustness and computational efficiency of the model is illustrated.
Numerical experiments showed the applicability and efficiency of the model.
At the stage 7, tuning of parameter's model, it has tested efficiency of the model.
Last, the efficiency of the model is assessed in regard to time efficiency.
In order to increase the efficiency of the model the optimal orientation could be identified with 1° accuracy.
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efficiency of the predictions
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efficiency of the methodologies
efficiency of the specimen
efficiency of the templates
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benefits of the models
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data of the models
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com