模糊综合评价方法在桥型多方案选择中的应用

为了解决现阶段桥型多方案选择中过多依赖设计者经验,而不可避免的带来主观性与片面性的问题.针对桥型方案选择的多因素与模糊性特征,提出了模糊综合评价方法在桥型多方案选择中的应用,确定了影响桥梁选型的指标体系,介绍了该方法的应用模型与步骤,并结合实例详细介绍了这种方法的应用过程.结果验证了这一方法的简明性和实用性.有利于减少桥梁型式选择的失误,提高其客观性与合理性,以得出最佳方案.     

改性纤维素增强丙烯酰胺水凝胶的合成与拉伸性能研究

采用水媒法制备了低取代度羧甲基纤维素,并用接枝聚合法制备了改性纤维素/丙烯酰胺水凝胶,考察了单体质量比、取代度等对水凝胶拉伸性能的影响.结果表明:对于接枝聚合反应,采用低取代度羧甲基纤维素可以提高纤维素的有效用量;当交联剂用量为180 mg/L、引发剂1 300 mg/L、低取代度羧甲基纤维素和丙烯酰胺质量比在1∶4 ～ 1∶4.5之间、单体质量分数为30%时,合成水凝胶的拉伸强度达到0.28 MPa;在此基础上,适量添加15%的淀粉可使水凝胶拉伸强度达到0.47 MPa;添加1%二氧化钛可使水凝胶拉伸强度达到0.38 MPa.     

Loss of Curing Agent During Thin Film (Droplet) Curing of Thermoset Material

Recently, it has been reported by our group and others^1.2 that loss of curing agent is encountered during the curing of small droplets or thin films of amine cured epoxies. In our earlier study³ results were reported on loss of curing agent in small droplets used in conducting the rnicrobond, single fiber test for determination of interfacial shear strength (ISS). It was reported that use of a volatile curing agent (meta-phenylene diamine (m-PDA) with DGEBA resin) resulted in increasing amounts of curing agent being lost (as measured by T₈ of the cured droplets) with decreasing droplet size during the processing procedure. Droplets smaller than 150 micrometers were seen to lose up to 40% of the curing agent leading to alteration of the mechanical properties of the droplet and, therefore, causing measured values of ISS to be exceedingly low. Use of a less volatile curing agent (Jeffamine 700, a polyether diamine, Texaco Specialty Chemicals) in combination with DGEBA resin produced results which indicated that loss of curing agent was not occuring. This study was undertaken to show the relationships between film (or droplet) size and the amount of curing agent lost (during the processing) for three different aminecured epoxy systems.     

自适应B样条小波函数模糊距离测量方法

目的 双目测距和单目测距是目前常用的两种基于光学传感器的测距方法,双目测距需要相机标定和图像配准,计算量大且测量范围有限,而单目测距减少了对设备和场地的要求,加快了计算时间。为了解决现有的单目测距方法存在精度低、鲁棒性差等缺点,本文提出了一种基于单模糊图像和B样条小波变换的自适应距离测量方法。方法 引入拉普拉斯算子量化评估图像模糊程度,并根据模糊程度值自动定位阶跃边缘;利用B样条小波变换代替高斯滤波器主动模糊化目标图像,并通过分析图像模糊程度、模糊次数以及测量误差之间的关系模型,自适应地计算不同景物图像的最优模糊次数;根据最优模糊图像中阶跃边缘两侧模糊程度变化求解目标边缘和相机之间的相对距离。结果 本文方法与基于高斯模糊图像的距离测量方法相比精度更高,平均相对误差降低5%。使用不同模糊次数对同样的图像进行距离测量时,本文算法能够自适应选取最优模糊次数,保证所测量距离的精度更高。结论 本文提出的单视觉测距方法,综合了传统的方法和B样条小波的优点,测距结果更准确,自适应性和鲁棒性更高。     

A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network

This paper focuses on consensus reaching process (CRP) under social network in which the trust relationship expressed by linguistic information. A new feedback mechanism in social network group decision making (SN-GDM) is proposed, which mainly consists of the following two aspects: (1) The propagation of distributed linguistic trust is investigated to study trust relation among experts; (2) A maximum self-esteem degree based feedback mechanism is developed to produce personalized advice for reaching higher group consensus. To do so, a novel linguistic trust propagation method is proposed to obtain the complete trust relationship among group. The self-esteem degree is used to define the extent that an individual makes concessions. Then, a maximum self-esteem degree based optimal feedback mechanism is built to produce personalized advice to help inconsistent experts make change of their opinion. Its novelty lies in the establishment of an optimization model with the nonlinear group self-esteem degree function as the objective function while group consensus threshold as the restrictions. Therefore, the inconsistent experts will reach a group consensus with the minimum loss of self-esteem degree, and then, it achieves the optimal balance between individual self-esteem and group consensus. Finally, a ranking process is applied to derive the appropriate consensus solution.     

当前我国在学位价值取向上的错位现象及其原因透视

学位具有学术价值、教育价值、管理价值等本体性价值，也具有个体价值与社会价值、工具性价值和目的性价值等派生性价值。当前人们在学位价值取向上存在着一些明显的错位和偏差。其具体表现有四点：一是重学位的“派生”性价值，轻学位的“本体”性价值；二是过分强调学位的教育价值和管理价值，而缺乏对学术价值应有地位的肯定；三是重学位的社会价值，轻学位的个体价值；四是重学位的工具性价值而忽视学位的目的性价值。导致这种错位现象产生的原因，不仅有教育系统内部因素，而且也与中国传统文化价值观和当前社会对人才的选拔、聘用政策有着直接的关系。     

基于支持向量机的炒作微博识别方法

微博是舆论传播的中心和渠道,同时参与舆论的形成、发展与引导过程,其自媒体发布、意见领袖参与等因素在一定程度上造成了微博谣言、虚假炒作、社会动员等现象。针对炒作微博的传播特点,分析其群体的隐蔽策划现象,挖掘出普通微博和炒作微博在传播网络结构、转发增量统计等方面的差异。通过社交网站的应用程序接口对目标微博的所有评论、转发和点赞用户进行信息获取,构建该微博的传播网络,利用社团模块度、平均最短路径和网络直径这3个属性度量该网络的紧密程度,基于支持向量机对所抽取的微博进行分类,进而识别出炒作微博。实验结果表明,该方法对微博传播用户的属性信息依赖小以及传播网络结构特征敏感,并且具有较高的炒作微博识别准确率。     

一种基于改进支持度的节能型WSNs数据融合算法

无线传感器网络(WSNs)内有大量的冗余数据,它们消耗了过多的网络能量;目前的数据融合算法对数据彼此间的联系考虑得不够充分,融合精度有待提高.针对上述问题,提出了一种基于改进支持度的节能型数据融合算法.该算法在网络的感知节点根据设定的阈值对采集到的数据进行初次融合,并引入自支持度的概念,与灰色接近度理论相结合改进支持度函数,将改进的支持度函数应用到汇聚节点计算最终的数据融合估计值.使用Matlab进行仿真的结果表明:该算法可节能27.87％,数据融合的温度绝对误差均值约为0.98℃,达到了节能和提高融合精度的目的.     

基于区间多目标量子文化算法的无线传感器网络覆盖能效优化

针对不确定环境下无线传感器网络覆盖能效优化问题,提出一种传感器节点区间感知模型;进而考虑网络覆盖率和节点冗余率,将其转化为区间多目标优化问题。基于一种新型区间个体依可能度占优关系,提出区间多目标量子文化算法,根据区间占优个体信息提取隐含知识,用于指导量子个体更新及进化个体变异与选择。不同环境下的仿真结果表明：基于所提出算法获得的Pareto解具有更好的收敛性、分布性和延展性;相应的无线传感器网络布局更合理。     

红外瓦斯传感器检测中噪声点研究

针对红外瓦斯传感器检测瓦斯浓度时易受到温度、压力等物理环境的影响而存在检测浓度值不准确的问题,提出一种结合分化距离与K-means算法方法找出瓦斯浓度数据集中的噪声点.该方法混合了分化距离和K-means算法的优点.对实验设计的传感器采集的瓦斯浓度数据集进行距离分化;运用K-means算法与孤立度系数结合法找出采集数据集中的噪声点并直接丢弃噪声点;通过均值法计算瓦斯浓度.实验结果表明:测量误差小于1％,精度高.