Title :
Evolutionary optimization in ANFIS for intelligent navigation system
Author :
Sivasankari, N. ; Malleswaran, M.
Author_Institution :
Dept. of EEE, Anna Univ., Tirunelveli, India
Abstract :
Global Positioning System (GPS) and Inertial Navigation System (INS) data can be integrated 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. Use of Artificial Intelligence (AI) techniques for an intelligent navigation system has been developed as an alternative to the conventional Kalman filter approach, in which it is mandatory to model the entire system. Many AI techniques have been implemented for the same, in which the use of ANFIS instead of neural networks and fuzzy logic has been widely implemented. In this paper Memetic optimization on ANFIS (MANFIS) has been proposed which outperforms Genetically optimized ANFIS (GANFIS).
Keywords :
Global Positioning System; Kalman filters; artificial intelligence; evolutionary computation; fuzzy logic; inertial navigation; information technology; neural nets; traffic engineering computing; AI techniques; GANFIS; GPS/INS data integration problem; Kalman filter approach; MANFIS; artificial intelligence techniques; evolutionary optimization; fuzzy logic; genetically optimized ANFIS; global positioning system; inertial navigation system; intelligent navigation system; memetic optimization on ANFIS; neural networks; Artificial intelligence; Biological cells; Global Positioning System; Memetics; Optimization; Sociology; Statistics; Adaptive Neuro Fuzzy Inference System(ANFIS); Genetic optimized ANFIS(GANFIS); Global Positioning System(GPS); Inertial Navigation System(INS); Memetic Algorithm(MA); Memetic optimized ANFIS(MANFIS);
Conference_Titel :
Recent Trends in Information Technology (ICRTIT), 2013 International Conference on
Conference_Location :
Chennai
DOI :
10.1109/ICRTIT.2013.6844259
