对当前工程建设监理工作存在问题的探究

随着我国经济的不断发展,工程建设监理领域也不断地得到丰富与完善,地位日益提升,作用日益重要.但它作为一个起步较晚的领域,受许多方面的影响,毕竟还存在着不少有待发展的地方.所以对它进行积极性的探究尤其显得必要.本文即着眼于现实和未来,从监理影响到的因素和影响到监理的因素这个角度去探究我国当前工程建设监理存在的问题,提出、分析问题,求得解决办法,力求这一问题得以明朗化.     

复杂系统诊断问题的研究

本文基于复杂系统的定义和特点,详细地讨论了复杂系统诊断问题中的概念体系,并在此基础上,根据复杂系统的层次性和故障产生与传播的机理,提出了复杂系统诊断问题的层次因果模型.该模型的中心思想是将复杂系统诊断问题分解成有限个层内诊断与层间诊断的循环交迭求解过程.     

关于林业土地评价

<正> 农林业的主要内容都是如何合理利用土地,充分发挥土地潜力以获得预期的产品与效益,满足社会需要。林业土地利用有其特点,首先是长期性,从获得产品及发挥效益来说,都需要较长时间,利用方式一旦实施后,持续时期很长。其次是多种功能性,除考虑主要受益面外,还要考虑其他受益面,特别是自然保护作用。此外,林业的经营集约度差异很大。为实现永续利用,又需在时间和空间上对土地利用做出合理安排。因此,在什么样的土地上采用什么利用方式,是林业生产中最重要的决策之一。为了尽量做到合理利用林业土地,充分发     

集成节约覆盖集理论和模糊概率推理的方法

本文运用Bayes定理分析了各种故障发生的先验概率对在已知征兆下判断故障的准确性的影响情况;论述了使用模糊概率描述征兆、故障、征兆与故障之间的映射关系等的方法;在将模糊概率和节约覆盖集理论集成的基础上,提出了基于浅知识的新的诊断推理方法.该方法在一定程度上减小了获取有关概率知识的难度,并对概率值的定义误差有一定的容错能力.     

"问题解决"与创造性思维

阐明“问题解决”的涵义;论述了“问题解决”是一个创造性的思维活动;针对我国传统数学教学模式在培养学生创造性思维能力方面存在的弊端,提出了运用“问题解决”教学,培养学生创造性思维能力的具体措施．     

彩色多普勒超声诊断肝血管瘤的临床价值研究

目的：探讨彩色多普勒超声在诊断肝血管瘤中的应用价值.方法：应用B型超声、彩色多普勒超声血流图（CDFI）和能量图（CDE）对72例肝血管瘤的检查结果进行分析.结果：CDFI对于直径大于1cm的肝血管瘤能显示血流信号,对直径小于1cm的小血管瘤不显示血流信号,而CDE对于直径小于1cm的小血管瘤也可显示血流信号.结论：彩色多普勒超声对肝血管瘤的诊断有较高的临床应用价值,CDE在肝小血管瘤病灶内的彩色血流显示方面优于CDPI.     

基于统计分析的交通检测设备性能诊断方法

针对智能交通(ITS)应用系统中检测设备长期性能的健康监测问题,在海量实测交通数据的分析挖掘基础上,提出了一套定量化的诊断方法.该方法以稳定性良好的实测交通流参数——自由流车速为主要指标,采用参数估计、假设检验与置信区间分析相结合的方式,完成针对检测数据的量化分析和检测设备性能状态判断.利用浮动观测车,在上海城市快速道路交通监控系统所积累的历史和实时数据中验证了该方法的有效性.     

System dynamics as a systems-based problem-solving methodology

Systems dynamics is concerned with using systems ideas to increase understanding of various types of phenomena and to aid in the decision-making which determines action upon the processes involved. Developments within system dynamics have occurred mainly independently of advances in the broader systems movement. In this paper an attempt is made to bring to bear on system dynamics some recent work which considers the character of systems-based problem-solving methodologies. System dynamics is placed within a framework which enables the relative strengths and weaknesses of different approaches to be identified. This leads to a deeper understanding of some of the critiques of system dynamics and enables some issues to be outlined which may help to strengthen the theoretical base of system dynamics methodology and hence improve its ability to tackle practical situations.     

1983年梅雨期中一次暴雨天气过程的诊断分析

1983年6月23—25日,长江流域出现了一次大范围的连续性暴雨过程。本文采用等熵面分析探讨了这一过程的基本特征。结果指出,四股气流,两股暖湿气流分别来自太平洋副高西侧和孟加拉湾,两股变性的西伯利亚干冷气流分别经蒙古西部,甘肃和我国东北、朝鲜、黄海,在31°N附近汇合成东—西向的辐合带是这次暴雨过程产生的有利条件。110°E附近的低空南风急流和30°N附近的低空西南风急流对这一过程的发展起了促进作用,而暴雨过程中凝结潜热释放对低空急流的发展起了一定的反馈作用。另外,在这一过程中低层水汽水平输送主要来自南海,而中下层水汽水平输送主要来自孟加拉湾。     

Gene association study with SVM, MLP and cross validation for diagnosis of diseases

Gene association study is one of the major challenges of biochip technology both for gene diagnosis where only a gene subset is responsible for some diseases, and for the treatment of the curse of dimensionality which occurs especially in DNA microarray datasets where there are more than thousands of genes and only a few number of experiments （samples）. This paper presents a gene selection method by training linear support vector machine （SVM）/nonlinear MLP （multilayer perceptron） classifiers and testing them with cross-validation for finding a gene subset which is optimal/suboptimal for the diagnosis of binary/multiple disease types. Genes are selected with linear SVM classifier for the diagnosis of each binary disease types pair and tested by leave-one-out cross-validation; then, genes in the gene subset initialized by the union of them are deleted one by one by removing the gene which brings the greatest decrease of the generalization power, for samples, on the gene subset after removal, where generalization is measured by training MLPs with leaveone-out and leave-four-out cross-validations. The proposed method was tested with experiments on real DNA microarray MIT data and NCI data. The result shows that it outperforms conventional SNR method in the separability of the data with expression levels on selected genes. For real DNA microarray MIT/NCI data, which is composed of 7129/2308 effective genes with only 72/64 labeled samples belonging to 2/4 disease classes, only 11/6 genes are selected to be diagnostic genes. The selected genes are tested by the classification of samples on these genes with SVM/MLP with leave-one-out/both leave-one-out and leave-four-out cross-validations. The result of no misclassification indicates that the selected genes can be really considered as diagnostic genes for the diagnosis of the corresponding diseases.