重载列车优化操纵算法设计与仿真

文章针对电力牵引重载列车的运行特点,对重载列车的优化操纵问题进行了分析研究,设计了一种基于模糊预测和再优化的列车运行控制算法。该算法先使用模糊逻辑控制器产生操纵队列,预测列车未来一段区间的运行情况,然后对产生的操纵队列以安全、节能为目标进行反复优化。算法通过对操纵队列的有重合区间局部寻优来保证得到近似全局最优解。文章使用列车牵引计算模型对算法进行了仿真验证,结果表明该算法产生的操纵队列基本达到了重载列车运行要求。     

多分类支撑向量机综述

支撑向量机的研究是当前人工智能领域的研究热点。传统的支撑向量机是两类的分类器,如何将其有效地推广到多类问题仍是一个有待研究的问题。在本文中,作者对目前已有的多分类支撑向量机算法,从基本思想、实现的方法、特点以及存在的问题上做了详细的介绍,以期对今后的研究有所启发。     

多级模糊综合评判在公路设计方案比选中的应用

应用多层模糊综合评判数学模型，对公路线路设计方案进行综合比选，克服了过去那种单凭经验选择方案的弊病，使公路线路的设计方案比选更加科学化、合理化。     

水利工程中进度控制的风险评估

分析影响施工进度的因素，并以施工方因素为例建立模糊风险评价集。利用模糊综合评价法对水利工程中影响施工进度的因素进行定量的风险评估，得出施工方各因素对施工进度影响的定量值，可以达到有效减小风险的效果。     

充液弯管的模态频率计算

考虑管道与液体之间的泊松耦合与连接耦合，推导了低频情况下的充液弯管轴向、横向振动的传递矩阵，并在给定的边阶条件的情况下推导出用传递矩阵求解弯管模态频率的方法。最后，用传递矩阵法和Ansys有限元分析软件计算了一定边界条件下充液弯管的模态频率。结果表明，固液耦合作用可使弯管的模态频率降低。     

现代控制理论与交流电机调速(Ⅱ)--智能控制(1)

人工智能系统将进一步与电力电子学以及运动控制相结合而更加深刻地影响后者的发展。特别是在研制高质量的传动和伺服控制装置中。文章着重介绍模糊逻辑控制、神经网络控制以及它们的交叉结合的神经网络-模糊控制系统及其应用与设计。     

国土开发型铁路投资效果的模糊层次评价法研究

国土开发型铁路在铁路投资中占据越来越重要的地位,此类铁路的效益除铁路企业盈利外主要表现为外部收益,也就是铁路建设对沿线地区政治、经济、社会、生态环境的影响,所以如何全面衡量国土开发型铁路的投资效果成为影响决策的主要问题。本文通过构建国土开发型铁路投资效果评价指标体系,运用模糊层次法建立评价模型,并以南疆铁路为例予以实证。     

Multivariate assimilation in MERCATOR project: New statistical parameters from forecast error estimation

The new operational prototype of Mercator (french Global Ocean Data Assimilation Experiment contribution) is composed of a North Atlantic primitive equation ocean model OPA (Ocean Parallel Algorithm between 20°S and 70°N, [Madec, G., P. Delecluse, M. Imbard and C. Lévy (1998). OPA8.1 ocean general circulation model reference manuel. Notes du pôle de modélisation IPSL. n°11: 91p]) and of a multivariate and multidata assimilation scheme [De Mey, P. and M. Benkiran (2002). “A multivariate reduced-order optimal interpolation method and its application in Mediterranean basin-scale circulation.” Ocean Forecasting : Conceptual basis and application, Pinardi, N., Springer Verlag.] This system has already given some significant improvements from previous Mercator configurations (M. Benkiran, personal communication). However some biases on ocean state still remain in the tropics where the reduced-order optimal interpolation scheme is suspected to be ill-parameted in the model forecast error. Indeed the guess error covariance matrix is decomposed into an error variance value and a spatio-temporal correlation function which are assumed to have some “good” properties (spatial homogeneity of the correlation function, constant ratio between signal and error variance). This study shows how we can use ensemble methods to validate these assumptions. We can see that the correlation function can reach negative values locally, mostly in regions of high variability contradictory with the homogeneous hypothesis. The reduced space used in the operational configuration is based on the signal seasonal Empirical Orthogonal Functions (EOFs). An empirical relationship between signal and error variance has been set and the correlation function is the same on every dimension of the reduced space. By projection of the estimated guess error variance onto the reduced space, we find a repartition of this quantity quite different to what was set in the system. The error statistics is found to be inhomogeneous compared to hypothesis made in the assimilation scheme. These two new parameters tested separately in the assimilation scheme gives significant improvements of the forecast and analysis results. This is particularly obvious in the tropics. But relationship between signal and error statistics (as assumed in the optimal interpolation) is found to be complex.     

供应商选择问题的模型和算法

针对供应商选择问题中的不确定因素,采用模糊随机参数进行刻画,并建立了模糊随机期望值模型,最终设计遗传算法进行求解,为合理地选择供应商及资源的优化配置提供了新的有效途径。     

基于模糊综合评价的编组站分类研究

首先回顾我国铁路编组站分类的历史及现状,然后从编组站分类问题的模糊性出发,确定适当的判断指标集,并利用模糊数学的综合评价模型对多项指标进行综合评价,从而为编组站的分类提供一种量化途径。