Extended Reflexive Ontologies for the Generation of Clinical Recommendations

Decision recommendations are a set of alternative options for clinical decisions (e.g., diagnosis, prognosis, treatment selection, follow-up, and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a “reasoning over domain” approach for the generation of decision recommendations by gathering and inferring conclusions from production rules. In order to rationalize our approach, we present a specification that will sustain the logic models supported in the knowledge bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey toward the solution of the reported needs. The starting point of our approach is the proposition of Reflexive Ontologies (RO). Here, we go a step further, proposing an extension of RO that includes the handling and reasoning that production rules provide. Our approach speeds up the recommendation generation process.     

基于T-S 模糊模型的采样数据网络控制系统H∞ 输出跟踪控制

研究具有采样数据的基于T-S (Takagi-Sugeno) 模糊模型网络控制系统H输出跟踪控制问题. 提出将采集器端数据采样周期、数据传输时滞和数据丢包转换为零阶保持器端数据更新周期, 在此基础上, 利用输入时滞法和PDC (Parallel distributed compensation) 技术, 建立网络环境下被控对象和参考模型合并的基于T-S 模糊模型的增广系统模型. 通过Lyapunov 方法, 并充分利用采样特性, 给出系统实现H输出跟踪的充分条件, 以及可靠模糊控制器的设计. 仿真结果表明所设计模糊控制器能够实现该类系统良好的跟踪.     

Fuzzy Structure of Complex Belief Systems: Fuzzy Relations and Fuzzy Belief Sets

In previous work, Nescolarde-Selva and Usó-Doménech (2014a Nescolarde-Selva, J. and J. L. Usó-Doménech. “Semiotic Vision of Ideologies.” Found Sci 19 (2014a): 263–282.[Crossref], [Web of Science ®] , [Google Scholar], b) discussed the theory that complex belief systems have a topological structure. In this article it is suggested that this structure is also fuzzy. We introduce the concepts of fuzzy sets in the context of beliefs (substantive and derived), and between derived beliefs themselves. Also introduced are the concepts of fuzzy covering and fuzzy invariance and the relationships between them.     

一种基于信号强度的室内定位干扰抑制新方法

针对WiFi、蓝牙等基于信号强度的室内定位技术易受遮挡、反射等影响,导致较大定位误差的问题进行研究.在室内信号传播模型的基础上,推导出基于信号传播模型的场强测距模型,根据该模型对现有定位解算中的牛顿迭代算法进行改进,对不同信号计算不同权值,采用加权最小二乘法求解,在不增加解算复杂度的情况下,提高定位精度.仿真表明,该算法抑制干扰能力强,有效提升了定位精度.     

低成本MEMS陀螺实时滤波方法

为找到一种普遍适合低成本MEMS陀螺仪的随机误差实时处理方法,利用Allan方差分析法首先对MEMS陀螺仪进行分析,根据其误差特性进而设计了平均滤波算法以剔除粗大误差,然后使用最小二乘法,通过拟合前一段历史结果得到下一时刻输出的预测值,基于以上工作最终设计出Kalman滤波器对所输出进行滤波。由于将最小二乘法的推测作为预测过程,避免了系统状态模型难以准确建立的问题。该方法动态性能好,具有普适性。实验结果证明,该方法在静态和动态下均能有效工作,滤波后常值漂移被有效补偿,角度随机游走不再占误差的主要成分,均方差小于滤波前的十分之一。     

Variable precision intuitionistic fuzzy rough set model and applications based on conflict distance

Due to the complexity and uncertainty of the physical world, as well as the limitation of human ability to comprehend, it is very difficult for any single method of uncertainty to effectively deal with the decision‐making problem that exists in real life. So, it is natural for us to think about incorporating the advantages of various theories of uncertainty to develop a more powerful hybrid method of soft decision‐making. In view of this recognition, the thought and method of intuitionistic fuzzy sets and variable precision rough sets are used to construct a novel intuitionistic fuzzy rough set model. With respect to the fact that the information system is intuitionistic fuzzy, the idea of measuring intuitionistic fuzzy similarity is used to define conflict distance. After that, this concept is combined with the variable precision rough sets so that a variable precision intuitionistic fuzzy rough set model is established, and its properties are investigated. After proposing an attribute reduction algorithm based on variable precision intuitionistic fuzzy rough sets, a case study is used to verify the feasibility and effectiveness of our novel model. The results show that our model indeed improves the classification ability of earlier models and possesses some ability to tolerate faults through adjusting the parameter λ and the confidence threshold β; it realizes the correct classification and extracts the decision rules.     

Fuzzy rough set on probabilistic approximation space over two universes and its application to emergency decision‐making

Probabilistic approaches to rough sets are still an important issue in rough set theory. Although many studies have been written on this topic, they focus on approximating a crisp concept in the universe of discourse, with less effort on approximating a fuzzy concept in the universe of discourse. This article investigates the rough approximation of a fuzzy concept on a probabilistic approximation space over two universes. We first present the definition of a lower and upper approximation of a fuzzy set with respect to a probabilistic approximation space over two universes by defining the conditional probability of a fuzzy event. That is, we define the rough fuzzy set on a probabilistic approximation space over two universes. We then define the fuzzy probabilistic approximation over two universes by introducing a probability measure to the approximation space over two universes. Then, we establish the fuzzy rough set model on the probabilistic approximation space over two universes. Meanwhile, we study some properties of both rough fuzzy sets and fuzzy rough sets on the probabilistic approximation space over two universes. Also, we compare the proposed model with the existing models to show the superiority of the model given in this paper. Furthermore, we apply the fuzzy rough set on the probabilistic approximation over two universes to emergency decision‐making in unconventional emergency management. We establish an approach to online emergency decision‐making by using the fuzzy rough set model on the probabilistic approximation over two universes. Finally, we apply our approach to a numerical example of emergency decision‐making in order to illustrate the validity of the proposed method.     

Multiattribute decision making based on intuitionistic fuzzy interaction average operators: a comparison

This paper proposes a new family of intuitionistic fuzzy information aggregation operators for multiattribute decision making. Such aggregate operators provide an excellent complement to the existing ones. In this study, comparison with existing intuitionistic fuzzy aggregation operators is presented in detail. Properties and special cases of the proposed operators are investigated. Finally, we introduce an approach to intuitionistic fuzzy multiattribute decision making. An example of the recruitment of intern candidates is illustrated to show the feasibility and superiority of the proposed method.     

基于科研合作网络的自动审稿人选择研究

主要研究科研合作网络（scientific collaboration network ,SCN）中选择审稿人的2个核心问题：网络构建和社区聚类。基于杂志论文的审稿人主要来自本杂志作者及审稿人应尽量评审与自己无关的科研工作这2个事实,通过论文中作者的排名计算所有作者之间的合作关系,构建归一化科研合作网络。考虑到网络中边的稀疏性,设计了合作压缩感知算法来计算不同作者间的社区类型,进行科研合作社区聚类。在模拟数据及2个真实期刊作者库上开展了多个实验。由于没有一个客观标准去评估所选出审稿人的合适性,通过网络中顶点连接矩阵的自动聚类性评估所构建科研网络的性能,通过作者合作团体的检测准确性来评价审稿人挑选的有效性。从实验结果可以看出,提出的网络构建方法具有较好的顶点聚类性;和经典算法相比,合作压缩感知社区检测算法在检测速度和稳定性方面具有很大的优势,审稿人挑选正确率提高了大约60％。     

受限模糊网络可信近邻查询

针对不确定网络环境下的近邻查询问题,给出一种新的解决方法.将不确定网络建模为模糊图,定义模糊图中两点间的可信最短路径距离和可信最短路径期望距离,在可信距离基础上,提出模糊图可信近邻查询概念,并给出网络距离受限条件下的模糊图可信近邻查询算法和即时可信近邻查询算法.算法采用模糊模拟方法降低问题难度,使用网络距离约束缩小搜索空间,运用优先队列快速得到满足精度ε要求的可信近邻查询结果.算法的时间复杂度分别为O((2r +Ar)(e+nlgn)+hlgh+ lgn)和O(e+ (n+1)lgn).理论分析与实验结果表明,可信近邻查询算法能够从模糊角度解决不确定网络环境下的近邻查询问题.