基于级差最大化组合赋权法的地下水功能评价

针对地下水功能评价中单独采用主观赋权法或客观赋权法存在的问题,结合二者的优点,采用基于主观赋权的层次分析法与客观赋权的熵权法相结合的级差最大化组合赋权法评价地下水功能,并通过计算不同赋权方法权重结果与平均值的相对偏差来衡量级差最大化组合赋权法的准确性。将该方法应用于伊犁河谷西北部平原区浅层地下水功能评价,评价结果基本符合评价区实际情况,验证了该评价方法在地下水功能评价中的可行性。     

基于Shannon熵的飞机交流发电机振动分析

飞机交流发电机是飞机关键部件之一,监测其健康状况具有重要意义。通过设计实验数据获取平台采集交流发电机在转速上升(从6000转/分到8500转/分)、平稳运行(7500转/分)及转速下降(8500转/分到6000转/分)三个阶段的振动信号,利用符号序列Shannon熵的计算方法以及符号化方法设定合适参数对振动信号进行了处理,得出了交流发电机在三个阶段的振动信号的Shannon熵;通过初步的分析表明,交流发电机在正常状态下三个阶段的Shannon熵都比较有规律的在一定范围内变化,一旦发生振动异常将会引起Shannon熵突变;经过分析讨论,Shannon熵的突变与否是可以用来反映交流发电机在机械方面是否存在故障隐患的。     

Improved results on frequency‐weighted balanced truncation and error bounds

In this paper, we present some new results on frequency‐weighted balanced truncation which is a significant improvement on Lin and Chiu's frequency‐weighted balanced truncation technique. The reduced‐order models, which are guaranteed to be stable in the case of double‐sided weighting, are obtained by direct truncation. Two sets of simple, elegant and easily calculatable a priori error bounds are also derived. Numerical examples and comparison with other well‐known techniques show the effectiveness of the proposed technique. Copyright © 2011 John Wiley & Sons, Ltd.     

Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment

We study the group decision making problem under intuitionistic fuzzy environment. Based on entropy and cross entropy, we give two methods to determine the optimal weights of attributes, and develop two pairs of entropy and cross entropy measures for intuitionistic fuzzy values. Then, we discuss the properties of these measures and the relations between them and the existing ones. Furthermore, we introduce three new aggregation operators, which treat the membership and non-membership information fairly, to aggregate intuitionistic fuzzy information. Finally, several practical examples are presented to illustrate the developed methods.     

The induced generalized aggregation operators for intuitionistic fuzzy sets and their application in group decision making

In this paper, we present the induced generalized intuitionistic fuzzy ordered weighted averaging (I-GIFOWA) operator. It is a new aggregation operator that generalized the IFOWA operator, including all the characteristics of both the generalized IFOWA and the induced IFOWA operators. It provides a very general formulation that includes as special cases a wide range of aggregation operators for intuitionistic fuzzy information, including all the particular cases of the I-IFOWA operator, GIFOWA operator and the induced intuitionistic fuzzy ordered geometric (I-IFOWG) operator. We also present the induced generalized interval-valued intuitionistic fuzzy ordered weighted averaging (I-GIIFOWA) operator to accommodate the environment in which the given arguments are interval-valued intuitionistic fuzzy sets. Further, we develop procedures to apply them to solve group multiple attribute decision making problems with intuitionistic fuzzy or interval-valued intuitionistic fuzzy information. Finally, we present their application to show the effectiveness of the developed methods.     

An information-theoretic approach to the written transmission of old English

Information theory offers a means for analyzing some constraints on the reading and copying process in Old English. Entropy for strings of various lengths offers a baseline measure of the uncertainty involved in transmission of Old English texts, while avoiding the pitfalls of applying models of modern reading to early medieval practice. Analysis of lengthy prose and verse texts in Old English revealed uniformly high values for entropy at all string lengths. High entropies may be the result of the language's irregular orthography, poetic koiné, and several dialects and imply that the language may have been easy to write but difficult to read. The low redundancy of the language which its high entropy values indicate suggests that the reader of Old English played an enhanced role in decoding a text and may provide an explanation for the high variability in the transmission of Old English verse.Katherine O'Brien O 'Keeffe is Professor of English at Texas A&M University and a co-director of its Interdisciplinary Group for Historical Literary Study.William Rundell is Professor of Mathematics at Texas A&M University.     

Vague集的新模糊熵

本文指出了现有Vague集模糊熵定义的不足,分析了其存在不足的根本原因,给出了Vague集模糊熵的公理化定义,提出了一种新的Vague集模糊熵的计算方法,并证明了其合理性和有效性。     

Study on structure and magnetic entropy changes of Ce2-xPrxFe16.5Co0.5 alloys

A series of Ce2-xPrxFe16.5Co0.5 alloys were preparedby arc melting under purified argon atmosphere. The structure and magnetic entropy changes in Ce2-xPrxFe16.5Co0.5 alloys were investigated by means of X-ray diffraction pattern and MPMS XL-7 magnetometer. The experimental results show that the crystal structure of Ce2-xPrxFe16.5Co0.5 alloys keeps in TH2Zn17-type rhombohedral, and the Curie temperature of Ce2-xPrxFe16.5Co0.5 alloys can be shifted to room temperature around by a composition adjustment. The magnetic entropy changes (-ΔSM) in Ce2-xPrxFe16.5Co0.5 alloys are relatively large, and a platform of magnetic entropy changes appearsnear the temperature TC. Ce2-xPrxFe16.5Co0.5 alloys are the potential working media for magnetic refrigeration with their stable chemical properties and especially low price.     

GIL机械故障诊断与预警技术研究

为了有效诊断气体绝缘金属封闭输电线路(GIL)的机械故障,搭建了110 kV GIL试验平台并设计了3种典型机械故障,通过互补集合经验模态分解(CEEMD)模糊熵值与鲸鱼优化极限学习机(WOA-ELM)模型联合方法对GIL机械故障模式进行识别与诊断。首先,利用CEEMD方法对振动信号进行分解,引入正负白噪声组对信号进行处理,得到含有故障信息的模态分量(IMF)。其次,利用模糊熵计算模态分量特征值,得到能表征故障特征的模糊熵值。最后,结合WOA-ELM模型对特征向量集进行模式识别,根据聚类结果与自适应阈值对GIL设备机械故障进行诊断和预警。结果表明,利用CEEMD与模糊熵对GIL振动信号特征进行分析,可以有效避免模态混叠和冗余噪声分量的干扰,得到能够表征故障特征的特征值;利用WOA-ELM模型可以有效实现GIL设备机械故障诊断与预警。     

Accurate Receptor-Ligand Binding Free Energies from Fast QM Conformational Chemical Space Sampling

Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical ‘Geometry, Frequency, Noncovalent, eXtended Tight Binding’ (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent ‘Statistical Assessment of the Modeling of Proteins and Ligands’ (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios.