{"title":"JIS:自动扶梯车厢列车的害虫种群预测","authors":"K. Yeow, Matthias Becker","doi":"10.1109/IEEM.2018.8607724","DOIUrl":null,"url":null,"abstract":"Pest population prognosis helps the growers in the greenhouse to keep the pest population below the threshold efficiently. INSIM is one of the recognized pest population simulators. However, the implementation of the INSIM simulation faces some difficulties to be executed as a web service. Thus, we propose a Java-based web application using the mathematical model used in INSIM. Additionally to the known model, our implementation is able to give prognosis boundaries based on uncertainty of the temperature development and pest count. The proposed JIS gives lower and upper estimation of the pest population with the mean accuracy of 66.67% against our experimental validation data. Furthermore, the relationship between the area coverage for each yellow sticky trap and its accuracy percentage is investigated.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"JIS: Pest Population Prognosis with Escalator Boxcar Train\",\"authors\":\"K. Yeow, Matthias Becker\",\"doi\":\"10.1109/IEEM.2018.8607724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pest population prognosis helps the growers in the greenhouse to keep the pest population below the threshold efficiently. INSIM is one of the recognized pest population simulators. However, the implementation of the INSIM simulation faces some difficulties to be executed as a web service. Thus, we propose a Java-based web application using the mathematical model used in INSIM. Additionally to the known model, our implementation is able to give prognosis boundaries based on uncertainty of the temperature development and pest count. The proposed JIS gives lower and upper estimation of the pest population with the mean accuracy of 66.67% against our experimental validation data. Furthermore, the relationship between the area coverage for each yellow sticky trap and its accuracy percentage is investigated.\",\"PeriodicalId\":119238,\"journal\":{\"name\":\"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM.2018.8607724\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2018.8607724","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
JIS: Pest Population Prognosis with Escalator Boxcar Train
Pest population prognosis helps the growers in the greenhouse to keep the pest population below the threshold efficiently. INSIM is one of the recognized pest population simulators. However, the implementation of the INSIM simulation faces some difficulties to be executed as a web service. Thus, we propose a Java-based web application using the mathematical model used in INSIM. Additionally to the known model, our implementation is able to give prognosis boundaries based on uncertainty of the temperature development and pest count. The proposed JIS gives lower and upper estimation of the pest population with the mean accuracy of 66.67% against our experimental validation data. Furthermore, the relationship between the area coverage for each yellow sticky trap and its accuracy percentage is investigated.