CPC G05B 19/408 (2013.01) [G06N 3/08 (2013.01); G05B 2219/45076 (2013.01)] | 16 Claims |
1. A method for operating canister purge comprising:
obtaining a set of inputs, by a processor, pertaining to one or more features used to predict purge vapor characteristics of an intake system of a vehicle;
obtaining data, by the processor, from sensors about a vehicle's intake system for use by a neural network to enable the processor to classify the set of inputs comprising the one or more features for a purge flow control for use in predicting a presence of purge content in the vehicle's intake system, wherein the neural network comprises a convolution neural network (CNN) for classifying, by the processor, the set of inputs to predict the purge content in the vehicle's intake system;
obtaining, by the processor, an output from the neural network wherein the output is configured as a binary output to instruct a vehicle controller to execute an action of an injector fueling command;
applying, by the processor, a convolution function of a first, a second, and a third layer of the CNN to classify the set of inputs composed of the one or more features into one or more feature matrices with size reductions for configuring a fuel control action based on the binary output and
applying, by the processor, a first dense function to vectorize a feature matrix received from an output from the third layer wherein a first dense function flattens the feature matrix into a single connected vector for configuring the fuel control action based on the binary output.
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