Precision Marketing Scheme based on Integrating Spatio-temporal Data Clustering and Neural Network

Liu, Su Ying

doi:10.1088/1742-6596/1087/3/032014

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…Clustering. e massive data are normalized and analyzed by K-means clustering [22]. M1 and M2 are simplified business data sets, and the ordered data are processed based on neural network, so as to obtain accurate spatiotemporal data [23].…”

Section: Spatiotemporal Datamentioning

confidence: 99%

Social Media Marketing Optimization Method Based on Deep Neural Network and Evolutionary Algorithm

Bian¹

2021

Scientific Programming

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Under the background of the vigorous development of China’s market economy, the marketing mix is constantly updated, which promotes the all-round development of various industries. Social media marketing has formed a relatively solid theoretical and practical foundation, especially with the continuous updating and iteration of Internet technology and the improvement of people’s requirements for experience, and we must find ways to optimize the methods of social media marketing. This study mainly introduces several optimization methods of social media marketing based on deep neural networks and advanced algorithms, and the experiments of gradient-based back-propagation algorithm and adaptive Adam’s optimization algorithm show that the proposed optimization algorithm can easily achieve the global optimal state based on the combination of back-propagation algorithm and Adam’s optimization algorithm. Accuracy of marketing is very important, so we introduce a scheme of how to accurately market, and the scheme is effective. Firstly, the FCE model is constructed by a three-layer back-propagation neural network, and then, the data input layer is designed to achieve the effect of the model.

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Section: Spatiotemporal Datamentioning

confidence: 99%