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Intelligent Optimization of Diversified Community Prevention of COVID-19 Using Traditional Chinese Medicine
IEEE Computational Intelligence Magazine ( IF 10.3 ) Pub Date : 2020-11-01 , DOI: 10.1109/mci.2020.3019899 Yu-Jun Zheng , Si-Lan Yu , Jun-Chao Yang , Tie-Er Gan , Qin Song , Jun Yang , Mumtaz Karatas
IEEE Computational Intelligence Magazine ( IF 10.3 ) Pub Date : 2020-11-01 , DOI: 10.1109/mci.2020.3019899 Yu-Jun Zheng , Si-Lan Yu , Jun-Chao Yang , Tie-Er Gan , Qin Song , Jun Yang , Mumtaz Karatas
Traditional Chinese medicine (TCM) has played an important role in the prevention and control of the novel coronavirus pneumonia (COVID-19), and community prevention has become the most essential part in reducing the risk of spread and protecting public health. However, most communities use a unified TCM prevention program for all residents, which violates the "treatment based on syndrome differentiation" principle of TCM and limits the effectiveness of prevention. In this paper, we propose an intelligent optimization method to develop diversified TCM prevention programs for community residents. First, we use a fuzzy clustering method to divide the population based on both modern medicine and TCM health characteristics; we then use an interactive optimization method, in which TCM experts develop different TCM prevention programs for different clusters, and a heuristic algorithm is used to optimize the programs under the resource constraints. We demonstrate the computational efficiency of the proposed method, and report the application results of the method in TCM-based prevention of COVID-19 in 12 communities in Zhejiang province, China, during the peak of the pandemic.
更新日期：2020-11-01
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