|Table of Contents|

Research on Text Classification Based on Convolutional Neural Network of Differential Evolution(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2022年01期
Page:
136-141
Research Field:
·计算机科学与技术·
Publishing date:

Info

Title:
Research on Text Classification Based on Convolutional Neural Network of Differential Evolution
Author(s):
Zhong Guifeng1; Pang Xiongwen2; Sun Daozong3
(1.College of Computer Science & Engineering,Guangzhou Institute of Science and Technology,Guangzhou 530631,China)(2.School of Computer Science,South China Normal University,Guangzhou 530631,China)(3.School of Electronic Engineering,South China Agricultural University,Guangzhou 530631,China)
Keywords:
classification; differential evolution; convolution neural network; scaling factor; convolution kernel
PACS:
TP391.1
DOI:
10.3969/j.issn.1001-4616.2022.01.019
Abstract:
In order to improve the performance of text classification,differential evolution convolutional neural network(CNN)algorithm was used for text classification. Firstly,the structural parameters of CNN were set randomly,then the parameters were optimized by differential evolution algorithm,and the optimal individuals were obtained by continuous evolution through crossover and selection. In order to enhance the applicability of differential optimization,the change of scaling factor was associated with evolutionary algebra,which solved the problem of low optimization level caused by unreasonable setting of scaling factor. Convolutional neural network used the weight and threshold after differential optimization to train text classification,so as to obtain stable text classification results. Experimental results showed that by setting the crossover rate of differential evolution and convolution kernel size of convolution neural network reasonably,better classification accuracy performance can be obtained,RMSE value was lower,and applicability in text classification was high.

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