The generalized Dice similarity measures for Pythagorean fuzzy multiple attribute group decision making

The Pythagorean fuzzy set (PFS) is characterized by two functions expressing the degree of membership and the degree of nonmembership, which square sum of them is equal or less than 1. It was proposed as a generalization of a fuzzy set to deal with indeterminate and inconsistent information. In this study, we shall present some novel Dice similarity measures of PFSs and the generalized Dice similarity measures of PFSs and indicates that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute group decision-making models with Pythagorean fuzzy information. Then, we apply the generalized Dice similarity measures between PFSs to multiple attribute group decision making. Finally, an illustrative example is given to demonstrate the efficiency of the similarity measures for selecting the desirable ERP system.     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

人工监督神经网络在煤层裂缝发育区识别中的应用

针对在地震属性应用中难以精细识别煤层裂缝发育区边界的难题,开展了基于人工监督神经网络技术的煤层裂缝发育区应用研究。从地震资料中获取倾角导向体以提取高质量的地震属性,以多属性为指导进行人工拾取样点,并基于多层感知器进行神经网络机器训练学习,建立裂缝的最优属性集,拓展整体数据后获得裂缝概率体,从而识别划分出煤层裂缝发育区。该技术在山西阳泉新元矿区进行了应用,煤层裂缝发育区的识别结果明显优于属性直接识别,但勘探区内暂无钻井资料,预测效果还有待进一步验证。     

OPC统一架构框架下的针织装备信息模型

为了解决针织装备信息交互中数据的碎片化、半结构化和信息异构而导致的数据语义完备性低的问题,提出了采用OPC统一架构(OPC UA)框架下构建针织装备信息模型的方法。建立了针织装备3个维度的结构化语义信息,设计了形式化的信息建模过程,从数字化针织生产车间整体模型和针织装备结构的角度建立了针织装备信息模型,包含属性集、组件集、配置信息等结构,并从针织装备数据变化频度、数据优先级、相关性等方面对信息模型作了优化。对比了针对针织装备OPC UA服务系统的实现方式,利用UaExpert SDK开发了针织OPC UA信息模型独立服务器,并对针织装备信息模型的互联互通进行了测试。结果表明,在OPC UA框架下构建的针织装备信息模型实例的方法是可行的,其在模型架构、语义结构、技术实现方面均有改进,并具有语义完备性高的特点。     

粒子群属性聚类的位置隐私保护

针对基于位置服务中连续查询情况下，用户自身属性信息很容易被攻击者获取，并通过关联获得用户位置隐私的情况，提出了一种利用粒子群聚类加速相似属性用户寻找，并由相似属性匿名实现用户位置泛化的隐私保护方法。该方法利用位置隐私保护中常用的可信中心服务器，通过对发送到中心服务器中的查询信息进行粒子群属性聚类，在聚类的过程中加速相似属性用户的寻找过程，由相似属性用户完成位置泛化，以此实现位置隐私保护。实验结果证明，这种基于粒子群属性聚类的隐私保护方法具有高于同类算法的隐私保护能力，以及更快的计算处理速度。     

天平与砝码计量标准考核中需注意的几个问题

笔者多年在天平与砝码计量标准考核工作中,经常遇到对考核规范理解有误造成计量标准延误考核,现列举几种常见现象并提出解决办法,供建标单位参考。     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.     

Analysis and improvement of the influence of sample shape on Pu measurement results

ABSTRACT

The analysis method of Fast Neutron Multiplicity Counting (FNMC) plays an increasingly important role in the measurement of nuclear material properties. Based on the assumption of point model, fast neutron multiplicity measurement equation is derived which can be used to measure the mass of Pu sample. However, the deviation of the simulated measurement of 1 kg Pu sample reaches 16.6% and increases with mass. Because nonpoint source samples of different shapes do not fully satify the hypothesis. To correct this deviation, a set of fast neutron multiplicity counters was built by Geant4 to simulate and study the mass attribute of Pu samples.The cylindrical sources of different shapes and different masses were simulated, the self-multiplication factor and α coefficient were corrected.And the corresponding third-order polynomial fitting equation was obtained, the goodness of fit was greater than 0.970. In the same way, the spherical and spherical shell source samples in the mass range of 0–5 kg were analyzed, the corrected mass deviation of samples was less than 10% in this interval. The results show that the combination of the fast neutron multiplicity counter and parameter correction can accurately measure the sample mass attribute.     

A Privacy-Preserving Attribute-Based Reputation System in Online Social Networks

Online social networks (OSNs) have revolutionarily changed the way people connect with each other. One of the main factors that help achieve this success is reputation systems that enable OSN users to ...