Hybrid neural-based decision level fusion architecture: application to road traffic collision avoidance
作者： Kurosh Madani , Abdennasser Chebira , Kamel Bouchefra , Thierry Maurin , Roger Reynaud
DOI: 10.1117/1.602015
关键词: Computer science 、 Fuzzy logic 、 Sensor fusion 、 Inference 、 Architecture 、 Smart system 、 Artificial neural network 、 Artificial intelligence 、 Classifier (UML) 、 Collision
摘要: A hybrid decision level architecture for a road collision risks avoidance system is presented. The goal of the to clas- sify behavior vehicles observed by smart or vehicle. knowledge vehicle enables best management resources. association model each mainly limitation inference and set actions be activated; thus interactions between levels can more intelligent. this composed neural classifier, which associated numerical classifier. Each these classifiers provides decisions that are expressed within framework fuzzy theory. An optimal fusion policy reached using functional network tool. © 1998 Society Photo-Optical Instrumentation Engineers. (S0091-3286(98)01202-1)
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