Title :
Application of Fuzzy Neural Networks Based on Genetic Algorithms in Integrated Navigation System
Author_Institution :
Dept. of Electr. Eng., Henan Univ. of Technol., Zhengzhou, China
Abstract :
There are matters of nonlinear, computing errors, dimension tragedy, and model errors in conventional data fusion algorithms in integrated navigation. Fuzzy neural networks based on genetic algorithms not only has the capacity of the fuzzy neural networks, such as expressing approximate and qualitative knowledge, study, and expressing nonlinear, but also has the competence of fast global searching of the genetic algorithms. So fuzzy neural networks based on genetic algorithms can be treated as an effective data fusion algorithms. And it was used in integrated navigation in this paper; the simulation results testified its validity.
Keywords :
fuzzy neural nets; genetic algorithms; navigation; sensor fusion; transportation; approximate knowledge; computing error; conventional data fusion algorithm; dimension tragedy; fast global searching competence; fuzzy neural network; genetic algorithm; integrated navigation system; model error; nonlinear error; qualitative knowledge; Computer networks; Design optimization; Function approximation; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Inertial navigation; Intelligent networks; Neural networks; Fuzzy neural networks; Genetic algorithms; Integrated navigation;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.393