{"title":"基于BP神经网络的物流项目风险评估——以非洲国家为例","authors":"Dafeng Xu, Tongtong Xu, Chunmei Liu, Jingbo Yang","doi":"10.1109/ICAICA50127.2020.9181941","DOIUrl":null,"url":null,"abstract":"In recent years, China's direct investments in Africa have grown substantially, making the risk analysis of direct investments by logistics companies increasingly important. Many specialised agencies in the world measure the national investment risk. However, their assessments only analyse the political and economic environment of each country without emphasising the importance of risk assessment in terms of logistics projects. This study fills the gap by presenting the risk assessment of logistics projects in 10 major African countries where China has the highest foreign direct investment. On the basis of existing research, an artificial neural network is mainly used to establish China's risk index system for African logistics projects and a macro early warning model for the investment risk of such logistics projects. Several suggestions on how to prevent the risks of logistics projects in African countries are provided.","PeriodicalId":113564,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Risk Assessment of Logistics Projects based on BP Neural Network: A Case Study on African Countries\",\"authors\":\"Dafeng Xu, Tongtong Xu, Chunmei Liu, Jingbo Yang\",\"doi\":\"10.1109/ICAICA50127.2020.9181941\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, China's direct investments in Africa have grown substantially, making the risk analysis of direct investments by logistics companies increasingly important. Many specialised agencies in the world measure the national investment risk. However, their assessments only analyse the political and economic environment of each country without emphasising the importance of risk assessment in terms of logistics projects. This study fills the gap by presenting the risk assessment of logistics projects in 10 major African countries where China has the highest foreign direct investment. On the basis of existing research, an artificial neural network is mainly used to establish China's risk index system for African logistics projects and a macro early warning model for the investment risk of such logistics projects. Several suggestions on how to prevent the risks of logistics projects in African countries are provided.\",\"PeriodicalId\":113564,\"journal\":{\"name\":\"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAICA50127.2020.9181941\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAICA50127.2020.9181941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Risk Assessment of Logistics Projects based on BP Neural Network: A Case Study on African Countries
In recent years, China's direct investments in Africa have grown substantially, making the risk analysis of direct investments by logistics companies increasingly important. Many specialised agencies in the world measure the national investment risk. However, their assessments only analyse the political and economic environment of each country without emphasising the importance of risk assessment in terms of logistics projects. This study fills the gap by presenting the risk assessment of logistics projects in 10 major African countries where China has the highest foreign direct investment. On the basis of existing research, an artificial neural network is mainly used to establish China's risk index system for African logistics projects and a macro early warning model for the investment risk of such logistics projects. Several suggestions on how to prevent the risks of logistics projects in African countries are provided.