Cargando…

Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning

In social science and natural science, MP (Marxist Philosophy) has played an active role in promoting its development, and MP also guides people's practice and understanding. There is an inevitable connection with system theory MP. In a sense, both system theory and PMbelong to methodology and...

Descripción completa

Detalles Bibliográficos
Autor principal: Jiang, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357689/
https://www.ncbi.nlm.nih.gov/pubmed/35958377
http://dx.doi.org/10.1155/2022/6322272
_version_ 1784763765477081088
author Jiang, Xiaoming
author_facet Jiang, Xiaoming
author_sort Jiang, Xiaoming
collection PubMed
description In social science and natural science, MP (Marxist Philosophy) has played an active role in promoting its development, and MP also guides people's practice and understanding. There is an inevitable connection with system theory MP. In a sense, both system theory and PMbelong to methodology and both contain the viewpoints of movement and development. In this paper, various text features in natural scenes are discussed in detail, and the original vector is studied by using CNN (Convective Neural Network) of DL (Deep Learning), so as to construct a one-dimensional text vector and realize the mutual influence and continuous optimization of feature extraction and text clustering. The experimental results show that under the condition of calculating the current cosine similarity measure, the accuracy rate is the highest, reaching 93.67%. This algorithm can effectively improve its performance in text classification tasks on large data sets.
format Online
Article
Text
id pubmed-9357689
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-93576892022-08-10 Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning Jiang, Xiaoming J Environ Public Health Research Article In social science and natural science, MP (Marxist Philosophy) has played an active role in promoting its development, and MP also guides people's practice and understanding. There is an inevitable connection with system theory MP. In a sense, both system theory and PMbelong to methodology and both contain the viewpoints of movement and development. In this paper, various text features in natural scenes are discussed in detail, and the original vector is studied by using CNN (Convective Neural Network) of DL (Deep Learning), so as to construct a one-dimensional text vector and realize the mutual influence and continuous optimization of feature extraction and text clustering. The experimental results show that under the condition of calculating the current cosine similarity measure, the accuracy rate is the highest, reaching 93.67%. This algorithm can effectively improve its performance in text classification tasks on large data sets. Hindawi 2022-07-31 /pmc/articles/PMC9357689/ /pubmed/35958377 http://dx.doi.org/10.1155/2022/6322272 Text en Copyright © 2022 Xiaoming Jiang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Jiang, Xiaoming
Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning
title Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning
title_full Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning
title_fullStr Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning
title_full_unstemmed Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning
title_short Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning
title_sort analysis of the relevance environment between marxist philosophy and system theory based on deep learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357689/
https://www.ncbi.nlm.nih.gov/pubmed/35958377
http://dx.doi.org/10.1155/2022/6322272
work_keys_str_mv AT jiangxiaoming analysisoftherelevanceenvironmentbetweenmarxistphilosophyandsystemtheorybasedondeeplearning