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Applying Embedded Hybrid ANFIS/Quantum-Tuned BPNN Prediction to Collision Warning System for Motor Vehicle Safety

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4 Author(s)
Bao Rong Chang ; Dept. of Comput. Sci. & Inf. Eng., Nat. Taitung Univ. ; Chung-Ping Young ; Hsiu Fen Tsai ; Jian-Jr Lin

This study is to explore how to realize high-performance collision warning system (CWS), providing the precaution against traffic crash in transit. An embedded hybrid adaptive network-based fuzzy inference system (ANFIS) plus quantum-tuned back-propagation neural network (QT-BPNN) built in the platform with DaVinci+XScale-NAV270 was employed to realize collision warning system and we also installed motor vehicle event data recorder (MVEDR). Finally, experiments and verification of the proposed approach were done successfully to achieve better accuracy and more effectiveness on warning level issuing and event data record to motor vehicle.

Published in:

Intelligent Systems Design and Applications, 2008. ISDA '08. Eighth International Conference on  (Volume:1 )

Date of Conference:

26-28 Nov. 2008