【摘要】 云模型是对语言值所蕴含的模糊性和随机性的一种数学描述,它用期望值、熵和超熵表征定性概念,将概念的模糊性和随机性集成在一起,能够实现定量与定性之间的相互转换,因而对交通信息的高度不确定性具有很强的鲁棒性.基于云模型提出的预测机制在一定程度上有效地解决了交通信息存在的模糊性和随机性问题,为交通信息预测提供了一种新的方法.检验结果表明预测值基本上与实际值吻合.更多还原

【Abstract】 The cloud model is a mathematical representation of fuzziness and randomness in linguistic concepts.The qualitative concept is represented by expected value,entropy and hyper entropy in this model.and It can realize the transformation between the qualitative and the quantitative when the fuzziness and randomness of a linguistic concept are integrated together.Therefore,it has strong robustness to the higher uncertain traffic information.A kind of traffic information forecast mechanism based on the cloud model is proposed.This mechanism can effectively overcome the fuzziness and the random in traffic information,and can offer a novel approach for traffic information forecasting.It also shows that the predicted results are basically in accord with the real ones.更多还原