隧道围岩稳定性改进模糊概率模型及其应用研究

为更加准确有效地判别隧道围岩稳定性,引入RandWPSO-LSSVM(随机权重粒子群算法-最小二乘支持向量机)围岩极限位 移预测模型,对传统模型的隶属函数进行优化,建立围岩稳定性改进模糊概率模型。基于改进模型方法,由围岩位移预测值u、预测 位移标准差、围岩极限位移预测值U 及预测极限位移标准差即可求解隧道围岩稳定概率,并结合8 个工程算例对模型进行验证。 结果表明,改进模型解决了传统模型隶属函数存在的极限位移取值范围不合理的问题,且有效消除了隶属函数线性简化处理导致 的偏差,由其计算的稳定概率与实际情况吻合较好,围岩稳定性评价结果的可靠性更高; 将改进模型应用于实际工程的隧道围岩 稳定性判别中,计算结果能够较好地反映实际工程情况。     

铁路调度指挥系统故障诊断方法

根据铁路调度指挥系统中的故障传播路径特点,建立故障传播的有向图及其模型,设计基于贝叶斯后验概率准则的故障诊断算法.该算法的基本原理是,每1个新增的故障现象都对应着1个故障原因域,依据贝叶斯后验概率准则,计算故障原因域中每1个故障原因的疑似概率,然后按其大小顺序插入既有的故障原因疑似概率集合中.随着故障现象的增加,当故障原因疑似概率集合不再改变时,运算终止.故障原因疑似概率集合中前n个元素能覆盖故障现象时,这n个元素所对应的故障原因,即是诊断结果.实验表明,在单故障模式和双故障模式下,运用这种故障诊断算法得出的结论完全正确,并且在计算机上的运算时间不超过0.8s.     

花岗岩残积土及全风化土标贯击数的概率分布

研究目的:研究花岗岩残积土的岩性特性,探讨花岗岩残积土及全风化土实测标贯击数N的概率分布,并计算其服从概率分布的概率密度函数.研究结论:目前国内外对标贯实测击数进行杆长修正没有一致意见,建议使用实测击数,可使野外编录、判别的操作性更强.通过实测结果来看,锤击数在15≤N＜30范围内可定名为残积土,锤击数在30＜N≤50范围内可定名为全风化土.经统计分析认为,深圳地区花岗岩残积土及全风化土实测标贯击数N的概型分布为正态分布.     

基于近似概率的衬砌结构耐久性设计研究

与其他建筑结构一样,隧道衬砌结构会因环境因素的侵蚀而产生耐久性损伤,从而影响使用寿命,这种环境损伤作用在传统隧道衬砌结构设计方法中未定量考虑。采用基于近似概率的方法对衬砌结构进行耐久性设计,在设计过程中定量考虑环境侵蚀作用,使结果更符合实际要求。最后通过算例进行进一步说明。结果表明,采用该方法能够在一定程度上提高结构的耐久寿命,是可行的。     

Understanding parking decisions with a Bayesian network

In this paper, a Bayesian network is developed to investigate three intertwining parking decisions, namely parking period, parking location, and parking duration, and the impacts of a number of parking-related factors on these decisions. With parking information from Beijing, China in 2005, the structure and parameter of a Bayesian network were learnt by employing the K2 algorithm and Bayesian parameter estimation method respectively. The results show that the decision on how long to park follows that on where to park, and both of them are affected by the decision of when to park. This suggests that parking policies aimed at intervening in one specific parking decision may have an indirect influence on other parking decisions, which embraces an integrated view in the development of parking policies. The findings facilitate the development of measures for regulating parking behavior by identifying important contributing factors.     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.     

基于快速贝叶斯网络的S700K转辙机故障诊断研究

转辙机故障对铁路运输安全和效益影响重大,针对转辙机故障原因与现象之间的复杂不确定性关系,提出一种基于粗糙集约简的高效贝叶斯网络故障诊断方法。首先,建立故障诊断决策表,利用改进的差别矩阵算法剔除对结果影响较小的属性,得到最简故障诊断决策表。其次,根据表中故障现象与故障类型连接关系建立贝叶斯网络模型,利用推理算法求解各类故障发生的概率。算法通过约简属性简化贝叶斯网络结构,降低算法复杂度,加快计算速度。最后,用某车站转辙机故障实例验证该智能故障诊断方法的正确性。     

东中国海波浪分布特征研究

以美国国家环境预报中心(NCEP)再分析气象资料作为驱动风场条件,运用第三代海浪模式WAM的第四版本(WAMC4)在西北太平洋海域建立二级嵌套波浪模型,利用连云港、冷家沙现场观测波浪资料对模型进行了验证,检验了该模型在东中国海波浪研究中的适用性针对东中国海进行了连续60年(1950—2909)的波浪后报模拟,在此基础上开展了东中国海波浪时空分布特征研究.结果表明:四季的平均有效波高等值线与岸线形状基本保持一致,且由南向北逐渐递减;有效波高分布的季节差异显著,冬季浪高最大,其次为秋季,春季、夏季最小。通过对比分析平均波浪要素和5%累积频率波浪要素的定量关系发现,在渤海范围内,5%累积频率有效波高与平均有效波高之比约为2.75,黄海与东海大部该比值则分别约为2.50和2.35,而5%累积频率平均周期与平均周期的比值在整个东中国海范围内约为1.45。     

基于本体论与贝叶斯式网络的舰炮武器系统故障诊断方法研究

针对舰炮武器系统在故障诊断过程中存在不确定性以及新故障知识不易添加的问题,提出了一种将本体论与贝叶斯网络相结合故障诊断方法。利用本体的知识表示方法建立关于舰炮武器系统的本体模型,然后将此模型转化为贝叶斯网络模型,最后利用贝叶斯网络进行舰炮武器系统故障方面的不确定性推理。利用此方法可以有效解决舰炮武器系统复杂故障现象问题。     

Study on Probability Plot Correlation Coefficient of the Log-Weibull Distribution

The log-Weibull distribution is a variant of the three-parameter Weibull distribution. The probability plot of a distribution model is desired since it can help to decide on whether the model is appropriate for fitting a given dataset and can provide the initial estimate of the model parameters. The decision on the appropriateness of a distribution is somehow subjective. This paper presents a probability plot of the log-Weibull distribution(LWPP). The distribution of the probability plot correlation coefficient is studied. From this distribution, a lower confidence limit is determined for determining whether the probability plot correlation coefficient derived from a given data set is large enough. The appropriateness and usefulness of this study are illustrated by two real-world examples.