Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence
With a large number of images provided by TV and other media flowing into the Internet and the reduction of technical barriers, images have not only become a daily practice for people to record their lives and communicate their behaviors but also become an important means for the public to express t...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2022/7723634 |
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| _version_ | 1832550419068354560 |
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| author | Ming Guo Weichen Jia |
| author_facet | Ming Guo Weichen Jia |
| author_sort | Ming Guo |
| collection | DOAJ |
| description | With a large number of images provided by TV and other media flowing into the Internet and the reduction of technical barriers, images have not only become a daily practice for people to record their lives and communicate their behaviors but also become an important means for the public to express their discourse in the cyberspace. Therefore, it is of great significance to analyze the image propagation algorithm using artificial intelligence. This paper mainly studies the algorithm analysis and governance of local media image propagation in the era of artificial intelligence. In this paper, the media is the research object, with its daily dissemination of video works as the research text, in order to discover the ethical problems in its dissemination activities as the purpose, integrating disciplinary knowledge to analyze the ethical problems in this art form, and trying to find out the fundamental measures to solve the problem. The advantages and disadvantages of the video recommendation intelligent algorithm based on the BP neural network are analyzed. By comparing different algorithms, it can be seen that the video recommendation accuracy of the BP neural network algorithm based on swarm optimization (FEBP) is 15.8% higher than that of the traditional BP neural network algorithm. These intelligent algorithms are added into the image transmission system, in order to achieve the goal of improving the image transmission and recommendation effect. |
| format | Article |
| id | doaj-art-6172969c7fc2458f894c80f5ce5dbd38 |
| institution | Kabale University |
| issn | 1754-2103 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-6172969c7fc2458f894c80f5ce5dbd382025-02-03T06:06:48ZengWileyApplied Bionics and Biomechanics1754-21032022-01-01202210.1155/2022/7723634Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial IntelligenceMing Guo0Weichen Jia1School of Culture and CommunicationSchool of Media and LawWith a large number of images provided by TV and other media flowing into the Internet and the reduction of technical barriers, images have not only become a daily practice for people to record their lives and communicate their behaviors but also become an important means for the public to express their discourse in the cyberspace. Therefore, it is of great significance to analyze the image propagation algorithm using artificial intelligence. This paper mainly studies the algorithm analysis and governance of local media image propagation in the era of artificial intelligence. In this paper, the media is the research object, with its daily dissemination of video works as the research text, in order to discover the ethical problems in its dissemination activities as the purpose, integrating disciplinary knowledge to analyze the ethical problems in this art form, and trying to find out the fundamental measures to solve the problem. The advantages and disadvantages of the video recommendation intelligent algorithm based on the BP neural network are analyzed. By comparing different algorithms, it can be seen that the video recommendation accuracy of the BP neural network algorithm based on swarm optimization (FEBP) is 15.8% higher than that of the traditional BP neural network algorithm. These intelligent algorithms are added into the image transmission system, in order to achieve the goal of improving the image transmission and recommendation effect.http://dx.doi.org/10.1155/2022/7723634 |
| spellingShingle | Ming Guo Weichen Jia Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence Applied Bionics and Biomechanics |
| title | Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence |
| title_full | Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence |
| title_fullStr | Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence |
| title_full_unstemmed | Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence |
| title_short | Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence |
| title_sort | local media image propagation algorithm and its governance in the age of artificial intelligence |
| url | http://dx.doi.org/10.1155/2022/7723634 |
| work_keys_str_mv | AT mingguo localmediaimagepropagationalgorithmanditsgovernanceintheageofartificialintelligence AT weichenjia localmediaimagepropagationalgorithmanditsgovernanceintheageofartificialintelligence |