试论《格萨尔》中的伦理思想与格萨尔理想人格

本分别就《格萨尔》史诗产生的社会历史背景、史诗中的社会理想范型、史诗中的道德评价标准以及对格萨尔是古代藏族人民的理想人格典范进行了论述。章指出，《格萨尔》中伦理思想的意蕴是丰富的。格萨尔其人的人格是伟大的，在批判地继承和弘扬藏族传统化的遗产时，很值得深入发掘和研究。     

高效液相色谱法测定奶粉中的β-胡萝卜素

采用高效液相色谱法测定奶粉中的β－胡萝卜素．奶粉样品在甲醇溶剂中碱化后，用石油醚萃取β－胡萝卜素，经Varian30cm×4mm硅胶柱分离，紫外检测定量．该方法最低检出限为5．38×10－10g，回收率为95．3％～98．4％，变异系数为2．04％．     

基于留数分析的模式发现算法的改进及其应用

文中提出了一种改进的知识发现算法. 针对基于留数分析和递归切割的模式发现算法的不足,在样本空间分割时,考虑到不同属性对知识发现的不同贡献,采取不同的离散化标准;在模式判别准则方面,改良后的算法随切割后产生的子空间数量动态调整模式判别准则. 在人造数据集和电力系统安全稳定评估中的应用结果验证了算法改进思路的合理性与有效性. 与原算法相比,改良后算法的知识发现效率更高、应用范围更广.     

温度对油、水、石英体系润湿性的影响

用量子场论方法计算了固 液界面的吸附自由能,导出了油、水、石英三相体系的润湿系数与温度的关系。计算表明,当系统的温度升高时,石英的亲水性增强,降低了多孔介质的残余油饱和度,这对热力采油机理研究有参考价值     

邻氨基噻唑偶氮类试剂质子化机理的研究

邻氨基噻唑偶氮类试剂［１～３］在不同酸度下呈现不同的颜色,关于其质子化发生的位置以及先后次序至今尚未见文献报道．本文通过量子化学计算,结合分光光度法对这类试剂质子化行为进行了研究．１实验方法１．１吸收光谱测定移取１．０ｍＬ１．０×１０－３ｍｏｌ／ＬＴ...     

大型地下空间综合交通枢纽中巨型斜柱长期沉降的监测及预测分析

结构及其重要构件的长期沉降是影响地下空间综合交通枢纽施工安全的关键因素之一,对其开展监测与预测具有重要的工程意义。以深圳市黄木岗大型地下空间综合交通枢纽为研究背景,采用自动化监测系统,首先监测了12轴巨型斜柱施工后的119期长期沉降,分析其长期沉降规律,并评判其预警状态。监测结果表明,斜柱施工后,长期的沉降规律为先在安全状态内小幅波动,再增大至黄色预警状态,最后在安全状态与预警状态之间小幅波动。然后,利用109期监测数据分别构建斜柱沉降的反向传播(back propagation, BP)神经网络模型和遗传算法-BP(genetic algorithm-BP,GA-BP)神经网络模型,并预测之后10期的斜柱累计沉降量以对比验证两种模型效果。结果表明,相比BP神经网络模型,GA-BP神经网络模型的预测值与实测值更吻合。     

Rough function model and rough membership function

Two pairs of approximation operators, which are the scale lower and upper approximations as well as the real line lower and upper approximations, are defined. Their properties and antithesis characteristics are analyzed. The rough function model is generalized based on rough set theory, and the scheme of rough function theory is made more distinct and complete. Therefore, the transformation of the real function analysis from real line to scale is achieved. A series of basic concepts in rough function model including rough numbers, rough intervals, and rough membership functions are defined in the new scheme of the rough function model. Operating properties of rough intervals similar to rough sets are obtained. The relationship of rough inclusion and rough equality of rough intervals is defined by two kinds of tools, known as the lower （upper） approximation operator in real numbers domain and rough membership functions. Their relative properties are analyzed and proved strictly, which provides necessary theoretical foundation and technical support for the further discussion of properties and practical application of the rough function model.     

Efficient combination rule of Dezert-Smarandache theory

The Dezert-Smarandache theory （DSmT） is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in data fusion and object recognition. However, there exist shortcomings in its combination rule. An efficient combination rule is presented, that is, the evidence＇s conflicting probability is distributed to every proposition based on remaining the focal elements of conflict. Experiments show that the new combination rule improves the reliability and rationality of the combination results. Although evidences conflict another one highly, good combination results are also obtained.     

Simulated annealing algorithm for the optimal translation sequence of the jth agent in rough communication

In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.     

Risk reduction in a project portfolio

The positive impacts of managing projects as a portfolio are quantified by comparing the value of the integrated risk of a project portfolio and the aggregation of single project risks implemented separately. Firstly, the integrated risk is defined by proposing risky events based on set theory. Secondly, as projects interact with each other in a project portfolio, the integrated risk is evaluated by using a Bayesian network structure learning algorithm to construct an interdependent network of risks. Finally, the integrated risk of a practical case is assessed using this method, and the results show that the proposed method is an effective tool for calculating the extent of risk reduction of implementing a project portfolio and identifying the most risky project, so as to assist companies in making comprehensive decisions in the phase of portfolio selection and portfolio controlling.