基于深度学习的林业信息文本分类算法研究
Research on the Text Classification Algorithm of Forestry Information Based on Deep Learning
邓辉1
作者信息
- 1. 广西壮族自治区国有七坡林场,广西南宁 530031
- 折叠
摘要
为提升林业文本数据处理与分类效率,采用深度学习方法设计一种林业信息文本分类算法,具体设计包括深度学习模型架构、数据预处理、特征提取层设计、序列处理与建模,旨在自动化管理林业信息.测试结果显示,该算法在准确性与速度上表现出色,可支持林业信息文本自动处理与深度分析.
Abstract
In order to improve the efficiency of forestry text data processing and classification,a forestry information text classification algorithm is designed by using deep learning method.The specific design includes deep learning model architecture,data preprocessing,feature extraction layer design,sequence processing and modeling,aiming at the automatic management of forestry information.The test results show that the algorithm performs well in accuracy and speed,and can support the automatic processing and in-depth analysis of forestry information text.
关键词
深度学习/分类算法/特征提取Key words
deep learning/classification algorithm/feature extraction引用本文复制引用
出版年
2024
NETL
NSTL
万方数据