为满足智能交通系统高性能模糊控制器设计的需要, 把粗集理论融入常规的模糊推理, 提出了一种交通控制模糊建模新方法, 利用粗集理论的知识推理, 直接从交通系统的测量数据提取模糊规则, 解决了城市交通模糊控制规则提取的瓶颈问题。实例分析表明:该方法简单有效, 不仅可以最大限度地减少从交警的经验直接提取模糊规则的局限性, 以获取最优的模糊模型, 同时建模方法具有普遍适用性, 提取的模糊规则更具客观性。该方法可以推广应用于多交叉口的模糊协调控制, 对于采用复杂算法的控制系统更能显示出其优越性。
Abstract
Combined rough sets theory and fuzzy reasoning together, a new method for modelling traffic fuzzy control systems is put forward to meet the needs of high performance fuzzy controller design applications of intelligent transportation systems.Authors extract the fuzzy control rules from historical traffic data by knowledge reasoning in rough sets theory and solve the bottle-neck problems for modelling urban traffic fuzzy control systems. The examples show that this method is simple and available as well as its objectivity. It can make the best of reducing the model inaccuracy due to the extraction of rules directly from the insufficient experience. It specially fits for the control systems with intricate algorithms and can be used in the fuzzy coordinated control of multi-intersections.
关键词
交通工程 /
交通控制 /
粗集理论 /
模糊规则
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Key words
traffic engineering /
traffic control /
rough sets theory /
fuzzy rule
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中图分类号：
U491.54
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参考文献
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