Automatic configuration of pump attributes of a Raman amplifier to achieve a desired gain profile

A system for configuring a raman amplifier, comprising:

• the raman amplifier having a plurality of raman pumps and a controller, the controller having a first processor and a first non-transitory computer readable memory storing instructions;
• a user device having a second processor and a second non-transitory computer readable memory storing second instructions that, when executed, cause the user device to accept input from the user of a desired gain profile;
• and
• a network administration device having a third processor and a third non-transitory computer readable memory storing third instructions that when executed cause the third processor to generate a machine learning model using machine learning techniques and deploy the machine learning model to the controller of the raman amplifier where the machine learning model is stored in the first non-transitory computer readable memory of the controller;
• wherein generating the machine learning model using machine learning techniques further comprises training a neural network by inputting a plurality of training datasets into the neural network, each of the plurality of training datasets having at least one training gain profile associated with configurations of a plurality of raman pumps configured to achieve the at least one training gain profile, wherein the neural network successively analyzes the plurality of training datasets and adjusts weights of connections between nodes in layers of the neural network to correct outputs until a corrected training output is accurate to with a margin of error when comprared to the configurations of the plurality of raman pumps associated with the at least one training gain profile;
• wherein the neural network is a feed-forward neural network, and wherein the layers of the feed-forward neural network comprises four layers of nodes including an input layer, a first hidden layer, a second hidden layer, and an output layer, wherein training the feed-forward neural network comprises assigning a weight to a connection between each of the nodes of the input layer, the first hidden layer, the second hidden layer, and the output layer;
• and
• wherein the desired gain profile is communicated from the user device to the controller of the raman amplifier where the first instructions cause the controller to automatically assess the desired gain profile using the machine learning model to determine raman pump configurations for each of the plurality of raman pumps of the raman amplifier and send the determined raman pump configuration to each of the plurality of raman pumps of the raman amplifier.