文献类型：期刊文献

英文题名：Import and export trade forecasting algorithm based on blockchain security and PSO optimized hybrid RVM model

作者：Wang, Yue

第一作者：王瑜

通信作者：Wang, Y[1]

机构：[1]Guizhou Inst Technol, Coll Econ & Management, Guiyang 550003, Guizhou, Peoples R China

第一机构：贵州理工学院

通信机构：corresponding author), Guizhou Inst Technol, Coll Econ & Management, Guiyang 550003, Guizhou, Peoples R China.|贵州理工学院;

年份：0

外文期刊名：SECURITY AND PRIVACY

收录：EI(收录号：20220911733358);WOS:【ESCI(收录号:WOS:000762661600001)】；

语种：英文

外文关键词：blockchain security; hybrid RVM model; import and export trade forecast; PSO algorithm

摘要：With the rapid development of globalization economy, countries in the world are more and more closely connected in business, and international import and export trade has also achieved rapid development. Based on the analysis of the status quo of the country's import and export trade, this article combines the main national economic indicators to analyze and study the algorithm of import and export trade forecasting. RVM is a sparse probability model and a new supervised learning method. Firstly, this paper introduces the protection system of block chain technology for import and export trade data information. Then, a hybrid RVM model is constructed, which is optimized by PSO algorithm, and the import and export volume is predicted based on this model. Based on the analysis of the data, it is tested that the security protection coefficient of the blockchain security technology for import and export trade data can reach up to 99.9%, and the accuracy of the import and export trade forecast based on the PSO optimized hybrid RVM model can reach up to 85.79%. A series of experiments show that the import and export trade forecast model studied in this paper can accurately predict the volume of import and export trade, thus providing a new method for the country's import and export trade, with high practical significance.