Research on resource allocation of drug safety supervision in Ningxia based on PSO-GM(1,1) and GRA
Keywords:
Particle Swarm Optimization, Grey Prediction Model, Grey Relational Analysis, Drug Safety Regulatory Resource AllocationAbstract
Drug quality and safety status is an important symbol of a country's economic development level and people's quality of life. In order to explore the resource allocation of drug safety supervision in Ningxia Hui Autonomous Region of China, this study used the particle swarm optimization GM(1,1) model to predict the relevant data of Ningxia Drug Administration in 2023. Grey relational analysis model was used to analyze the input and output of drug safety supervision in Ningxia from 2019 to 2023. The research results show that: in the past five years, Ningxia's drug safety supervision has achieved good output, but there are some problems in the allocation of regulatory resources, such as unfair allocation of drug supervision funds and other market supervision affairs costs, and excessive neglect of cosmetic affairs. Therefore, it is proposed to adjust the structure of general public service fees and increase the proportion of drug supervision funds. Adjust the fund structure of drug supervision and optimize the output of drug safety supervision; Standardize the annual report, and make government information open.
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APA:
Chen, H., Tong, Y., & Cai, Y. (2023). Research on resource allocation of drug safety supervision in Ningxia based on PSO-GM(1,1) and GRA. International Scientific Technical and Economic Research, 1(3), 1–14. http://www.istaer.online/index.php/Home/article/view/No.2311
GB/T 7714-2015:
Chen Huiyang, Tong Yueyue, Cai Yuke. Research on resource allocation of drug safety supervision in Ningxia based on PSO-GM(1,1) and GRA[J]. International Scientific Technical and Economic Research, 2023, 1(3): 1–14. http://www.istaer.online/index.php/Home/article/view/No.2311
MLA:
Chen, Huiyang, Yueyue Tong, and Yuke Cai. "Research on resource allocation of drug safety supervision in Ningxia based on PSO-GM(1,1) and GRA." International Scientific Technical and Economic Research, 1.3 (2023): 1-14. http://www.istaer.online/index.php/Home/article/view/No.2311
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