Yun Hwan Kim , Seong Joon Yoo , Yeong Hyeon Gu , Jin Hee Lim , Dongil Han , Sung Wook Baik
{"title":"基于回归和机器学习技术的作物害虫预测方法:综述☆","authors":"Yun Hwan Kim , Seong Joon Yoo , Yeong Hyeon Gu , Jin Hee Lim , Dongil Han , Sung Wook Baik","doi":"10.1016/j.ieri.2014.03.009","DOIUrl":null,"url":null,"abstract":"<div><p>This paper describes current trends in the prediction of crop pests using machine learning technology. With the advent of data mining, the field of agriculture is also focused on it. Currently, various studies, domestic and overseas, are under progress using machine learning technology, and cases of its utilization are increasing. This paper classifies and introduces SVM (Support Vector Machine), Multiple Linear Regression, Neural Network, and Bayesian Network based techniques, and describes some cases of their utilization.</p></div>","PeriodicalId":100649,"journal":{"name":"IERI Procedia","volume":"6 ","pages":"Pages 52-56"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ieri.2014.03.009","citationCount":"39","resultStr":"{\"title\":\"Crop Pests Prediction Method Using Regression and Machine Learning Technology: Survey\",\"authors\":\"Yun Hwan Kim , Seong Joon Yoo , Yeong Hyeon Gu , Jin Hee Lim , Dongil Han , Sung Wook Baik\",\"doi\":\"10.1016/j.ieri.2014.03.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper describes current trends in the prediction of crop pests using machine learning technology. With the advent of data mining, the field of agriculture is also focused on it. Currently, various studies, domestic and overseas, are under progress using machine learning technology, and cases of its utilization are increasing. This paper classifies and introduces SVM (Support Vector Machine), Multiple Linear Regression, Neural Network, and Bayesian Network based techniques, and describes some cases of their utilization.</p></div>\",\"PeriodicalId\":100649,\"journal\":{\"name\":\"IERI Procedia\",\"volume\":\"6 \",\"pages\":\"Pages 52-56\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.ieri.2014.03.009\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IERI Procedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212667814000100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IERI Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212667814000100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Crop Pests Prediction Method Using Regression and Machine Learning Technology: Survey
This paper describes current trends in the prediction of crop pests using machine learning technology. With the advent of data mining, the field of agriculture is also focused on it. Currently, various studies, domestic and overseas, are under progress using machine learning technology, and cases of its utilization are increasing. This paper classifies and introduces SVM (Support Vector Machine), Multiple Linear Regression, Neural Network, and Bayesian Network based techniques, and describes some cases of their utilization.
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