{"title":"基于遗传优化ANFIS的智能导航系统","authors":"M. Malleswaran, V. Vaidehi, R. A. Joseph","doi":"10.1109/ICOAC.2011.6165207","DOIUrl":null,"url":null,"abstract":"Global positioning System (GPS) and Inertial Navigation System (INS) data can be integrated together to provide a reliable navigation. This paper presents an approach of solving GPS/INS data integration problem, without the need of modeling the characteristics of GPS and INS sensors. This approach uses Genetically optimized Adaptive Neuro-Fuzzy Inference System (GANFIS) as an alternative to the conventional Kalman filter approach in which it is mandatory to model the entire system.","PeriodicalId":369712,"journal":{"name":"2011 Third International Conference on Advanced Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Genetically optimized ANFIS based Intelligent Navigation System\",\"authors\":\"M. Malleswaran, V. Vaidehi, R. A. Joseph\",\"doi\":\"10.1109/ICOAC.2011.6165207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Global positioning System (GPS) and Inertial Navigation System (INS) data can be integrated together to provide a reliable navigation. This paper presents an approach of solving GPS/INS data integration problem, without the need of modeling the characteristics of GPS and INS sensors. This approach uses Genetically optimized Adaptive Neuro-Fuzzy Inference System (GANFIS) as an alternative to the conventional Kalman filter approach in which it is mandatory to model the entire system.\",\"PeriodicalId\":369712,\"journal\":{\"name\":\"2011 Third International Conference on Advanced Computing\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Third International Conference on Advanced Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOAC.2011.6165207\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third International Conference on Advanced Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOAC.2011.6165207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetically optimized ANFIS based Intelligent Navigation System
Global positioning System (GPS) and Inertial Navigation System (INS) data can be integrated together to provide a reliable navigation. This paper presents an approach of solving GPS/INS data integration problem, without the need of modeling the characteristics of GPS and INS sensors. This approach uses Genetically optimized Adaptive Neuro-Fuzzy Inference System (GANFIS) as an alternative to the conventional Kalman filter approach in which it is mandatory to model the entire system.
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