Application of Artificial Intelligence in Precision Marketing

Yang, Xue; Hao-wen, LI; Ni, Likun; Li, Teng

doi:10.4018/joeuc.20210701.oa10

Cited by 53 publications

(27 citation statements)

References 22 publications

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“…Artificial intelligence technology is gradually affecting all aspects of our lives. Swarm intelligence evolutionary algorithms can deal with problems such as nonderivable node transfer functions or the absence of gradient information [ 9 , 10 ]. At the same time, it also promotes the development of all aspects of life [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Public View of Public Health Emergencies Based on Artificial Intelligence Data

Zhang¹,

Chu-ke²,

Kim

et al. 2022

Journal of Environmental and Public Health

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In the current environment where the network and the real society are intertwined, the network public view of public emergencies has involved in reality and altered the ecology of communal public views in China. A new online court of influence has been created, and it affected the trend of events. As the main type of public emergencies, public health emergencies are directly related to people’s health and life insurance. Therefore, the public often pays special attention. At present, correct media guidance plays an irreplaceable and important role in calming people’s hearts and stabilizing social order. If news and public view are left unchecked, it is likely to cause panic among the people. However, in reality, public view research has always been a research object that is difficult to intelligentize and quantify. Based on such a realistic background, the article conducts a research on public view of public health emergencies based on artificial intelligence data analysis. This study designs an expert system for network public view and optimizes the algorithm for the key problem: SFC deployment. Finally, the system was put into real news and public opinion research on new coronavirus epidemic prevention, and experimental tests were carried out. The experimental results have shown that in the new coronavirus incident, the nuclear leakage incident, and the epidemic prevention policy, the data obtained by the public through the Internet are 50%, 68.06%, and 64.35%, respectively. For the system function in this study, both ICSO and IPSO are far better than the optimization results of CSO and PSO. For most of the test functions, IPSO is better than ICSO’s optimization results, which better fulfills the needs of the research content. This study will make an in-depth analysis of the evolution process of online public opinion on public emergencies from the macro-, meso-, and micro-perspectives, in order to analyze the dissemination methods and internal evolution mechanism of various public emergencies of online public opinion, which provides countermeasures and suggestions for the government to guide and manage network public opinion.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Public View of Public Health Emergencies Based on Artificial Intelligence Data

Zhang¹,

Chu-ke²,

Kim

et al. 2022

Journal of Environmental and Public Health

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show abstract

“…With the rapid improvement of the domestic economy and the gradual implementation of the informatization strategy, the intelligence level of all walks of life in China has continued to develop, and various AI systems have been gradually established. These AI systems have penetrated into all fields of society and all aspects of people’s lives, such as e-commerce, computer medicine, mechanical engineering, games, and virtual simulation ( Yang et al, 2021 ; Zl et al, 2021 ). Figure 1 shows a field related to artificial intelligence.…”

Section: Design Methods Of Family Health Education Public Service Sys...mentioning

confidence: 99%

Artificial Intelligence-Based Family Health Education Public Service System

Zhao

2022

Front. Psychol.

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Family health education is a must for every family, so that children can be taught how to protect their own health. However, in this era of artificial intelligence, many technical operations based on artificial intelligence are born, so the purpose of this study is to apply artificial intelligence technology to family health education. This paper proposes a fusion of artificial intelligence and IoT technologies. Based on the characteristics of artificial intelligence technology, it combines ZigBee technology and RFID technology in the Internet of Things technology to design an artificial intelligence-based service system. Then it designs the theme of family health education by conducting a questionnaire on students’ family education and analyzing the results of the questionnaire. And it designs database and performance analysis experiments to improve the artificial intelligence-based family health education public service system designed in this paper. Finally, a comparative experiment between the family health education public service system based on artificial intelligence and the traditional health education method will be carried out. The experimental results show that the family health education public service system based on artificial intelligence has improved by 21.74% compared with the traditional family health education method; compared with the traditional family health education method, the health education effect of the family health education public service system based on artificial intelligence has increased by 13.89%.

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“…Designers must carefully test the accuracy and power consumption of safety function components when formulating the development process of intelligent safety clothing products. And it organically combines these properties with the basic elements of clothing, thus retaining other factors that may be equally important to consumers under the premise of emphasizing safety functions [20].…”

Section: Clothing Design Processmentioning

confidence: 99%

Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence

Zhou

Shi

2022

Journal of Advanced Transportation

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With the development of technologies in various fields, more and more technologies have been applied to safety clothing, which has led to the rapid development of safety clothing. The improvement of living standards is accompanied by the change of consumption concepts. Consumers’ requirements for clothing products have become more artistic, healthier, and more ecological, and they look forward to more and better safety clothing to meet their health needs. In this context, this article studies traffic safety outdoor clothing design based on big data (BD) and AI. This article introduces the design method of outdoor safety clothing for traffic based on BD and machine learning in artificial intelligence (AI) and did two experiments. To this end, this paper adopts a Deep Belief Network (DBN), which is trained layer by layer through Restricted Boltzmann Machine (RBM), and successfully solves the problems of lack of a large number of labeled samples and easy to fall into local optimum. The first experiment is to test the accuracy of various machine learning algorithms for clothing size measurement. The results obtained are as follows: the predicted value of the DBN neural network is the closest to the actual value, the average prediction accuracy of DBN for the cuff size is 90%, and the average prediction accuracy for the neck circumference is 91.5%. The second experiment is to investigate the functional needs and performance concerns of children and outdoor workers. The results of the experiment are as follows: for children, 79.9% of people want clothing to have a positioning function, which accounts for the highest proportion. For outdoor workers, the most important clothing function they need is eye-catching style, and 90.1% of those choose this option. In terms of clothing performance concerns, most people choose to care very much, and the second most people choose to care about comfort.

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Application of Artificial Intelligence in Precision Marketing

Cited by 53 publications

References 22 publications

[Retracted] Public View of Public Health Emergencies Based on Artificial Intelligence Data

[Retracted] Public View of Public Health Emergencies Based on Artificial Intelligence Data

Artificial Intelligence-Based Family Health Education Public Service System

Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence

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