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Fig. 5 Autonomous modulation classification flow for radar pulses.
The corresponding classification flow is carried out as follows.
Figure 6 shows the modulation family classification flow based on the MCA method.
Fig. 6 Modulation family classification flow chart based on the MCA method.
Both types of memories can be further classified based on the memory technology that they use and based on data volatility as shown in the classification flow chart depicted in Figure 2.
Based on dataset of membrane proteins, the classification flow chart was obtained as follows.
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The final trained model with the identification rule and criterion for the classification of flow units was used for identifying flow units in the cored and non-cored intervals of reservoir.
Classification of flow regimes in water management and hydroecological research has grown significantly in recent years.
A systematic classification of flow interference regimes is linked to the observed vortex shedding responses for a wide range of arrangements.
It is concluded that using the combination of the WT and LSSVM improved the accuracy of classification of flow units in the Minghuazhen Formation.
The feasibility of a transportable artificial neural network (ANN -based technique for the clANN -basedon of flow regimes in techniquese gas/liquid/pulp forer systhes by using pressure signals as input was examined.
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