RETRACTED: Local Media Image Propagation Algorithm and Its Governance in the Age of Artificial Intelligence (Retracted article. See vol. 2023, 2023)

被引:2
作者
Guo, Ming [1 ]
Jia, Weichen [2 ]
机构
[1] Guangdong Polytech Sci & Technol, Sch Culture & Commun, Zhuhai, Peoples R China
[2] Ningbo Tech Univ, Sch Media & Law, Ningbo, Peoples R China
关键词
TRANSMISSION;
D O I
10.1155/2022/7723634
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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.
引用
收藏
页数:6
相关论文
共 11 条
[1]   Supercritical water heat transfer coefficient prediction analysis based on BP neural network [J].
Ma, Dongliang ;
Zhou, Tao ;
Chen, Jie ;
Qi, Shi ;
Shahzad, Muhammad Ali ;
Xiao, Zejun .
NUCLEAR ENGINEERING AND DESIGN, 2017, 320 :400-408
[2]   Robust image alignment for cryogenic transmission electron microscopy [J].
McLeod, Robert A. ;
Kowal, Julia ;
Ringler, Philippe ;
Stahlberg, Henning .
JOURNAL OF STRUCTURAL BIOLOGY, 2017, 197 (03) :279-293
[3]   A Novel Energy Efficient Object Detection and Image Transmission Approach for Wireless Multimedia Sensor Networks [J].
Rehman, Yasar Abbas Ur ;
Tariq, Muhammad ;
Sato, Takuro .
IEEE SENSORS JOURNAL, 2016, 16 (15) :5942-5949
[4]   Temperature prediction of the molten salt collector tube using BP neural network [J].
Ren, Ting ;
Liu, Shi ;
Yan, Gaocheng ;
Mu, Huaiping .
IET RENEWABLE POWER GENERATION, 2016, 10 (02) :212-220
[5]   Discrete image data transmission in heterogeneous wireless network using vertical handover mechanism [J].
Salwe, Sagar Shriram ;
Naik, Karamtot Krishna .
IET IMAGE PROCESSING, 2017, 11 (07) :550-558
[6]  
Senthamilselvan K., 2016, CIRCUITS SYST, V7, P1816, DOI [10.4236/cs.2016.78156, DOI 10.4236/CS.2016.78156]
[7]   Efficient Image Transmission Schemes over Zigbee-Based Image Sensor Networks [J].
Tao Dan ;
Yang Guangwei ;
Chen Houjin ;
Wu Hao ;
Liu Pingping .
CHINESE JOURNAL OF ELECTRONICS, 2016, 25 (02) :284-289
[8]   Wind Power Interval Prediction Based on Improved PSO and BP Neural Network [J].
Wang, Jidong ;
Fang, Kaijie ;
Pang, Wenjie ;
Sun, Jiawen .
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2017, 12 (03) :989-995
[9]   Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method [J].
Wang, Shouxiang ;
Zhang, Na ;
Wu, Lei ;
Wang, Yamin .
RENEWABLE ENERGY, 2016, 94 :629-636
[10]   Error compensation based on BP neural network for airborne laser ranging [J].
Wu, Bing ;
Han, Shaojun ;
Xiao, Jin ;
Hu, Xiaoguang ;
Fan, Jianxin .
OPTIK, 2016, 127 (08) :4083-4088