کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1713305 | 1013220 | 2006 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Uncertain information fusion with robust adaptive neural networks-fuzzy reasoning1
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself (including fuzziness, randomness, incompleteness as well as roughness, etc). Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems Engineering and Electronics - Volume 17, Issue 3, September 2006, Pages 495-501
Journal: Journal of Systems Engineering and Electronics - Volume 17, Issue 3, September 2006, Pages 495-501
نویسندگان
Zhang Yinan, Sun Qingwei, Quan He, Jin Yonggao, Quan Taifan,