Method for predicting liquid holdup of moisture pipeline based on GA-BP neural network
A BP neural network and GA-BP technology, applied in the field of multiphase flow prediction, can solve problems such as poor prediction accuracy and unstable prediction, and achieve the effects of high accuracy, wide application range and fast speed
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[0033] The following is attached figure 1 The inventive method is described in further detail:
[0034] The method of predicting liquid holdup of wet gas pipeline based on GA-BP neural network, the calculation process is shown in figure 1 , the steps include:
[0035] Step 1: Determine the initial structure of the BP neural network
[0036] Generally, the design of neural network should give priority to 3-layer network (that is, there is 1 hidden layer). Increasing the number of hidden layers can reduce network error and improve accuracy, but it also complicates the network, thereby increasing the training time of the network and "over-fitting". together" tendency.
[0037] The neural network designed and used by the present invention is a 3-layer network.
[0038] A total of 6 influencing variables, such as the pipe diameter, pressure, gas velocity, liquid velocity, temperature, and liquid phase viscosity of the wet gas pipeline, are used as the input of the input layer o...
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