异质出行群体的合理划分是提升出行需求预测准确性和实施主动式交通管理的关键,针对目前城市多方式出行群体划分研究的不足,在分析出行习惯与偏好差异影响因素的基础上,提出基于潜在类分析(Latent Class Cluster Analysis,LCCA)的城市...异质出行群体的合理划分是提升出行需求预测准确性和实施主动式交通管理的关键,针对目前城市多方式出行群体划分研究的不足,在分析出行习惯与偏好差异影响因素的基础上,提出基于潜在类分析(Latent Class Cluster Analysis,LCCA)的城市异质出行群体识别方法.以北京市为例,应用揭示性偏好调查进行基础数据收集,运用Mplus软件编程实现LCCA模型估计.模型将出行者划分为三类异质出行群体,群体1:低出行+方式均衡组(20.4%),群体2:中高出行+小汽车偏好组(30.3%),群体3:高出行+绿色交通组(49.3%).模型回归结果表明:群体2、3的百分比与北京市小汽车、公共交通出行比例之差均不超过2%,证明提出的出行群体识别方法有效,个人属性、出行者对各交通方式的认知与态度对群体隶属影响显著.针对各异质出行群体提出了相应的绿色交通发展措施,为城市交管部门的精细化出行管控提供重要依据.展开更多
The vertices of an infinite locally finite tree T are labelled by a collection of i.i.d.real random variables{Xo}ver which defines a tree indexed walk So=∑X,.We introduce and study the oscillations of the walk.
As malign ventricular tachyarrhythmias triggering sudden cardiac death (SCD), both ventricular tachycardia (VT) and ventricular fibrillation (VF) are major causes of mortality. The most efficient ther- apy for SCD pre...As malign ventricular tachyarrhythmias triggering sudden cardiac death (SCD), both ventricular tachycardia (VT) and ventricular fibrillation (VF) are major causes of mortality. The most efficient ther- apy for SCD prevention is implantable cardioverter defibrillators (ICD). The ICD can accurately and ef- fectively identify the forthcoming of fatal ventricular tachyarrhythmias and deliver a shock in order to restore patients’ normal sinus rhythm. In this study, two nonlinear complexity measures based on en- tropy: approximate entropy (ApEn) and sample entropy (SampEn) as well as two time linear indices: the mean RR interval (the average of time intervals between consecutive R-waves) and the standard devia- tion of RR intervals were used for short-term forecasting of VT-VF occurrence. The last small sections of interbeat intervals preceding 135 VT-VF episodes from 78 patients stored by the ICD were analyzed and compared with individually acquired control time series (CON series) from the same patients, which are normally intrinsic sinus rhythms. The results demonstrate that in addition to an obvious in- crease in heart rates of the patients, the values of two entropy measures are significantly smaller for VT-VF episodes than those for CON series. Conclusions can be drawn that when a ventricular tach- yarrhythmia approaches, the sympathetic tone of the patients is increased, and the complexity of their RR intervals immediately before the onset of VT-VF events is obviously lower than that of RR intervals recorded during sinus rhythms. For a better separation, the optimal range of threshold r is determined for two algorithms. ApEn and SampEn measures might be the suitable nonlinear parameters for short- term prediction of life-threatening ventricular tachyarrhythmias in the application of the cardioversion and defibrillation.展开更多
文摘异质出行群体的合理划分是提升出行需求预测准确性和实施主动式交通管理的关键,针对目前城市多方式出行群体划分研究的不足,在分析出行习惯与偏好差异影响因素的基础上,提出基于潜在类分析(Latent Class Cluster Analysis,LCCA)的城市异质出行群体识别方法.以北京市为例,应用揭示性偏好调查进行基础数据收集,运用Mplus软件编程实现LCCA模型估计.模型将出行者划分为三类异质出行群体,群体1:低出行+方式均衡组(20.4%),群体2:中高出行+小汽车偏好组(30.3%),群体3:高出行+绿色交通组(49.3%).模型回归结果表明:群体2、3的百分比与北京市小汽车、公共交通出行比例之差均不超过2%,证明提出的出行群体识别方法有效,个人属性、出行者对各交通方式的认知与态度对群体隶属影响显著.针对各异质出行群体提出了相应的绿色交通发展措施,为城市交管部门的精细化出行管控提供重要依据.
文摘The vertices of an infinite locally finite tree T are labelled by a collection of i.i.d.real random variables{Xo}ver which defines a tree indexed walk So=∑X,.We introduce and study the oscillations of the walk.
基金the National Natural Science Foundation of China (Grant Nos. 60501003, 60701002)
文摘As malign ventricular tachyarrhythmias triggering sudden cardiac death (SCD), both ventricular tachycardia (VT) and ventricular fibrillation (VF) are major causes of mortality. The most efficient ther- apy for SCD prevention is implantable cardioverter defibrillators (ICD). The ICD can accurately and ef- fectively identify the forthcoming of fatal ventricular tachyarrhythmias and deliver a shock in order to restore patients’ normal sinus rhythm. In this study, two nonlinear complexity measures based on en- tropy: approximate entropy (ApEn) and sample entropy (SampEn) as well as two time linear indices: the mean RR interval (the average of time intervals between consecutive R-waves) and the standard devia- tion of RR intervals were used for short-term forecasting of VT-VF occurrence. The last small sections of interbeat intervals preceding 135 VT-VF episodes from 78 patients stored by the ICD were analyzed and compared with individually acquired control time series (CON series) from the same patients, which are normally intrinsic sinus rhythms. The results demonstrate that in addition to an obvious in- crease in heart rates of the patients, the values of two entropy measures are significantly smaller for VT-VF episodes than those for CON series. Conclusions can be drawn that when a ventricular tach- yarrhythmia approaches, the sympathetic tone of the patients is increased, and the complexity of their RR intervals immediately before the onset of VT-VF events is obviously lower than that of RR intervals recorded during sinus rhythms. For a better separation, the optimal range of threshold r is determined for two algorithms. ApEn and SampEn measures might be the suitable nonlinear parameters for short- term prediction of life-threatening ventricular tachyarrhythmias in the application of the cardioversion and defibrillation.
