{"title":"利用预测模型估计直升机飞行试验中获得的仪器数据","authors":"B. Coşkun, Burkay Genç","doi":"10.1109/EUROCON52738.2021.9535625","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a hybrid system consisting of decision trees and neural networks to calculate the measurement faults of sensor readings and to predict the actual values in a flight test of a helicopter in production. We present the architecture of the models, and extensive test results.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating Instrumentation Data Acquired During Flight Test of a Helicopter using Predictor Models\",\"authors\":\"B. Coşkun, Burkay Genç\",\"doi\":\"10.1109/EUROCON52738.2021.9535625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a hybrid system consisting of decision trees and neural networks to calculate the measurement faults of sensor readings and to predict the actual values in a flight test of a helicopter in production. We present the architecture of the models, and extensive test results.\",\"PeriodicalId\":328338,\"journal\":{\"name\":\"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EUROCON52738.2021.9535625\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUROCON52738.2021.9535625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimating Instrumentation Data Acquired During Flight Test of a Helicopter using Predictor Models
In this paper, we propose a hybrid system consisting of decision trees and neural networks to calculate the measurement faults of sensor readings and to predict the actual values in a flight test of a helicopter in production. We present the architecture of the models, and extensive test results.
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