Sentence examples for model architecture with from inspiring English sources

Open image in new window Fig. 1 Generalized ANN model architecture with input, hidden, and output layer.

The optimized model outperformed the previous model architecture with up to 55% performance improvement.

Fig. 4 The proposed recurrent neural network-based language model architecture with input layer segmented into three components: the prefix, the stem and the suffix.

By default, HMMER uses a maximum a posteriori (MAP) architecture algorithm to find the model architecture with the highest posterior probability for the alignment data.

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures, with complex structures, composed of multiple non-linear transformations [3, 5].

For the purposes of this study we pick model architectures with EDM and calculate the COR and PTV of these models separately.

The connectivity of the viable space indicates to what extent different model architectures with the same behavior can change into one another through small changes in individual parameters, as might occur on evolutionary time scales.

The many viable parameter points we found allowed us to characterize key properties of model architectures with individual or combined feedback loops via the geometry of the viable space.

This study describes a lumped kinetic modelling architecture with which to simulate and predict the pyrolysis reaction kinetics of hemicellulose biopolymers.

The present work improves on an existing model by optimizing the model architecture along with the key learning variables of the ANN and by making the model more generalizable to a wider variety of fuel candidate types, specifically the class of furans and furan derivatives, by including specific molecules for the model to incorporate.

Table 2 summarizes the accuracy obtained by the CNN RNN (with GRU neuron model) architecture, for different respective structures, with weights selected similarly, based on performance on the validation data set).