{"title":"基于支持向量机的国际贸易演变预测:以港口综合体为例","authors":"O. Imrani","doi":"10.1145/3454127.3456587","DOIUrl":null,"url":null,"abstract":"In this research work, we will present the main results and interpretations of the analysis of secondary data collected and processed. The analysis of Support Vector Machines, also known as Large Margin Separators (SVM), was used to predict the performance of the Tanger Med port, especially in terms of optimizing the logistics costs of the port, which allows a very strong evolution. level of international trade. The results of the SVM analysis obtained, helped to answer the problematic of our research, thus achieving the objectives of the study. The SVM technique was based on inferential analysis which showed the relevance of the results obtained from the secondary data and answered the research questions.","PeriodicalId":339898,"journal":{"name":"International Conferences on Networking, Information Systems & Security","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Prediction of international trade evolution through the Support Vector Machine: The case of a port complex\",\"authors\":\"O. Imrani\",\"doi\":\"10.1145/3454127.3456587\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this research work, we will present the main results and interpretations of the analysis of secondary data collected and processed. The analysis of Support Vector Machines, also known as Large Margin Separators (SVM), was used to predict the performance of the Tanger Med port, especially in terms of optimizing the logistics costs of the port, which allows a very strong evolution. level of international trade. The results of the SVM analysis obtained, helped to answer the problematic of our research, thus achieving the objectives of the study. The SVM technique was based on inferential analysis which showed the relevance of the results obtained from the secondary data and answered the research questions.\",\"PeriodicalId\":339898,\"journal\":{\"name\":\"International Conferences on Networking, Information Systems & Security\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conferences on Networking, Information Systems & Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3454127.3456587\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conferences on Networking, Information Systems & Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3454127.3456587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of international trade evolution through the Support Vector Machine: The case of a port complex
In this research work, we will present the main results and interpretations of the analysis of secondary data collected and processed. The analysis of Support Vector Machines, also known as Large Margin Separators (SVM), was used to predict the performance of the Tanger Med port, especially in terms of optimizing the logistics costs of the port, which allows a very strong evolution. level of international trade. The results of the SVM analysis obtained, helped to answer the problematic of our research, thus achieving the objectives of the study. The SVM technique was based on inferential analysis which showed the relevance of the results obtained from the secondary data and answered the research questions.