The influencing factors of community risk are complex. For the low accuracy of traditional prediction model, a multichannel convolutional neural network community risk prediction model is proposed by improving convolutional neural network of deep learning. First of all, in the community risk prediction model, the structure of multichannel input convolutional neural network is selected. Then, add it into the full connection layer. Subsequently, the DenseNet layer is added to establish connections between different network layers. Finally, the receptive field is improved, and the gradient disappearance is solved. Thus, the prediction accuracy of model is improved. Compared with the traditional model, the proposed multichannel convolutional neural network model has better prediction accuracy. In addition, it performs better on the three indicators, namely, correlation coefficient R , coefficient of determination R 2 , and mean square root error RMSE. Compared with the commonly used LSTM model and logic regression model, the proposed model also has certain advantages, which is more suitable for community risk prediction.

With the development of communication technology, the birth of 5G technology has epoch-making signi cance for data transmission and storage. Because of its very large network bandwidth and small network delay, it is very reliable in data transmission. 5G and other engineering, such as arti cial intelligence and other technologies are often linked together, from the technical means and data transmission e ciency and other aspects of the technical level, promote and make arti cial intelligence technology can be further expanded and extended. Based on this, the application and development of 5G technology and arti cial intelligence under the background of new era information technology are expanded and studied in this paper. In addition, based on the prediction process of deep neural network construction, this paper studies its operability on FPGA platform from this process, and carries out a series of related studies on the implementation means of neural network on FPGA platform. In this paper, an accelerated system is designed, and the model can be established based on the key factors extracted from the accelerated system. Applying models set under different acceleration systems in different scenarios can be suitable for different network architectures. In the nal research phase, we analyzed the materials and performed experimental veri cation. In the context of the market economy, we elaborated on the responsibility of the government in a certain region to maintain public security. For a region, it needs to be based on local actual conditions, speci c analysis of speci c issues, learning from the experience of some areas where public health incidents are handled well, and establishing a system with local characteristics. From the process of elaboration, we found that public health safety is not only closely related to each of our lives, but also further related to social stability and security.

With the development of communication technology, the birth of 5G technology has epoch-making significance for data transmission and storage. Because of its very large network bandwidth and small network delay, it is very reliable in data transmission. 5G and other engineering, such as artificial intelligence and other technologies are often linked together, from the technical means and data transmission efficiency and other aspects of the technical level, promote and make artificial intelligence technology can be further expanded and extended. Based on this, the application and development of 5G technology and artificial intelligence under the background of new era information technology are expanded and studied in this paper. In addition, based on the prediction process of deep neural network construction, this paper studies its operability on FPGA platform from this process, and carries out a series of related studies on the implementation means of neural network on FPGA platform. In this paper, an accelerated system is designed, and the model can be established based on the key factors extracted from the accelerated system. Applying models set under different acceleration systems in different scenarios can be suitable for different network architectures. In the final research phase, we analyzed the materials and performed experimental verification. In the context of the market economy, we elaborated on the responsibility of the government in a certain region to maintain public security. For a region, it needs to be based on local actual conditions, specific analysis of specific issues, learning from the experience of some areas where public health incidents are handled well, and establishing a system with local characteristics. From the process of elaboration, we found that public health safety is not only closely related to each of our lives, but also further related to social stability and security.

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