{"title":"人工神经网络微电池电场水平预测模型","authors":"A. Neskovic, N. Neskovic, D. Paunovic","doi":"10.1109/EURCON.2001.937780","DOIUrl":null,"url":null,"abstract":"A new microcell prediction model for the mobile telephone environment is presented. The principles of popular feedforward neural networks are used to build the model. Utilising a new artificial neural network (ANN) model some important disadvantages of both deterministic and statistical models can be overcome. In order to build the model, extensive electric field level measurements (in the 900 MHz frequency band) were carried out in the city of Belgrade, for two different test transmitter locations. The comparison between the data obtained by the proposed electric field level prediction model and the independent measurement sets have shown that the proposed model is accurate (on the order of the local mean measurement uncertainty) and reliable. At the same time, the algorithm is simple, fast and suitable for computer implementation.","PeriodicalId":205662,"journal":{"name":"EUROCON'2001. International Conference on Trends in Communications. Technical Program, Proceedings (Cat. No.01EX439)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"ANN microcell electric field level prediction model\",\"authors\":\"A. Neskovic, N. Neskovic, D. Paunovic\",\"doi\":\"10.1109/EURCON.2001.937780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new microcell prediction model for the mobile telephone environment is presented. The principles of popular feedforward neural networks are used to build the model. Utilising a new artificial neural network (ANN) model some important disadvantages of both deterministic and statistical models can be overcome. In order to build the model, extensive electric field level measurements (in the 900 MHz frequency band) were carried out in the city of Belgrade, for two different test transmitter locations. The comparison between the data obtained by the proposed electric field level prediction model and the independent measurement sets have shown that the proposed model is accurate (on the order of the local mean measurement uncertainty) and reliable. At the same time, the algorithm is simple, fast and suitable for computer implementation.\",\"PeriodicalId\":205662,\"journal\":{\"name\":\"EUROCON'2001. International Conference on Trends in Communications. Technical Program, Proceedings (Cat. No.01EX439)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EUROCON'2001. International Conference on Trends in Communications. Technical Program, Proceedings (Cat. No.01EX439)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EURCON.2001.937780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EUROCON'2001. International Conference on Trends in Communications. Technical Program, Proceedings (Cat. No.01EX439)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURCON.2001.937780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANN microcell electric field level prediction model
A new microcell prediction model for the mobile telephone environment is presented. The principles of popular feedforward neural networks are used to build the model. Utilising a new artificial neural network (ANN) model some important disadvantages of both deterministic and statistical models can be overcome. In order to build the model, extensive electric field level measurements (in the 900 MHz frequency band) were carried out in the city of Belgrade, for two different test transmitter locations. The comparison between the data obtained by the proposed electric field level prediction model and the independent measurement sets have shown that the proposed model is accurate (on the order of the local mean measurement uncertainty) and reliable. At the same time, the algorithm is simple, fast and suitable for computer implementation.