{"title":"Classification and Prediction of Interference Pathloss Measurements Inside B-757 Using Feed Forward Neural Networks (Prepared December 2005)","authors":"M. Jafri, J. Ely, L. Vahala","doi":"10.1109/CEFC-06.2006.1632993","DOIUrl":null,"url":null,"abstract":"Neural network modeling is introduced in this paper to classify and predict interference pathloss measurements on a Boeing 757 airplane. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structure and the aircraft system-of-concern. Modeled results are compared with measured data and a plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft","PeriodicalId":262549,"journal":{"name":"2006 12th Biennial IEEE Conference on Electromagnetic Field Computation","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 12th Biennial IEEE Conference on Electromagnetic Field Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEFC-06.2006.1632993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Neural network modeling is introduced in this paper to classify and predict interference pathloss measurements on a Boeing 757 airplane. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structure and the aircraft system-of-concern. Modeled results are compared with measured data and a plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft