{"title":"运筹学与机器学习:工程课程","authors":"Alvaro Talavera, Ana Luna","doi":"10.1109/EDUNINE.2019.8875770","DOIUrl":null,"url":null,"abstract":"In this work, we integrate computational techniques based on machine learning (ML) and computational intelligence (IC) to conventional methodologies used in the Operational Research (OR) degree course for Engineers. That synergy between those techniques and methods allows students to deal with complex problems. The main contribution of this paper is to present a different proposal for OR courses using the synergy between mathematical models employing computer simulations, IC and different hybrid models.","PeriodicalId":211092,"journal":{"name":"2019 IEEE World Conference on Engineering Education (EDUNINE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Operational Research and Machine Learning: An Engineering Course\",\"authors\":\"Alvaro Talavera, Ana Luna\",\"doi\":\"10.1109/EDUNINE.2019.8875770\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we integrate computational techniques based on machine learning (ML) and computational intelligence (IC) to conventional methodologies used in the Operational Research (OR) degree course for Engineers. That synergy between those techniques and methods allows students to deal with complex problems. The main contribution of this paper is to present a different proposal for OR courses using the synergy between mathematical models employing computer simulations, IC and different hybrid models.\",\"PeriodicalId\":211092,\"journal\":{\"name\":\"2019 IEEE World Conference on Engineering Education (EDUNINE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE World Conference on Engineering Education (EDUNINE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDUNINE.2019.8875770\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE World Conference on Engineering Education (EDUNINE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDUNINE.2019.8875770","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Operational Research and Machine Learning: An Engineering Course
In this work, we integrate computational techniques based on machine learning (ML) and computational intelligence (IC) to conventional methodologies used in the Operational Research (OR) degree course for Engineers. That synergy between those techniques and methods allows students to deal with complex problems. The main contribution of this paper is to present a different proposal for OR courses using the synergy between mathematical models employing computer simulations, IC and different hybrid models.