A method for optimizing a word vector based on a non-retention optimal individual genetic algorithm
A genetic algorithm and word vector technology, applied in the field of text generators, can solve problems such as the local optimal solution of the gradient descent algorithm, and achieve the effect of improving the robustness of the model
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[0029] The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.
[0030] A method of optimizing the word vector based on not retaining the optimal individual genetic algorithm of the embodiment, such as figure 1 The flow shown:
[0031] Step 1: Construct the word vector recurrent neural network model, randomly generate word vector weights and recurrent neural network values through the random function improved by c language, and create the weights of P word vector matrices as the population of the genetic algorithm, where P is The number of individuals in the population, where the set value of P is 50;
[0032] Step 2: Convert the word vector matrix to a one-dimensional chromosome: expand the weight of the word vector matrix W into a one-dimensional vector The number string, and use the number string as the chromosome in the genet...
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