Pessimistic Rough Decision

<正>With granular computing point of view,this paper first presents a novel rough set model with a multigranulation view,called pessimistic rough decision,where set approximations are defined through using consistent granules among multiple granular spaces on the universe.Then,we investigate several important properties of the pessimistic rough decision model.With introduction of the rough set model,we have developed two types of multigranulation rough sets(MGRS):optimistic rough decision and pessimistic rough decision. These multigranulation rough set models provide a kind of effective approach for problem solving in the context of multi granulations.     

确定减速器型谱系列最优方案的一种适用方法

型谱系列最优方案的确定，是一个大规模复杂系统问题。本文运用模糊数学中的相似优先比来建立齿轮减速器分传动比系列方案中各机型与最优单机间的模糊关系矩阵，通过取适当的入水平截集，就可找出一种既符合型谱要求、又与单机最优值最接近的系列最优方案，为解决这类问题提供了一种适用、可行的办法。     

下方图形

下方图形这一概念是为了说明非负函数可测的几何意义而引进的。它在证明某些积分定理中发挥了很大的功效。本文归纳、推导了下方图形的一些基本性质,并探讨它在证明一些积分定理上的应用。     

VOLVO PENTA柴油发电机组双层隔振降噪系统设计与验证

针对某钻井井场内的单层隔振的柴油发电机组振动噪声过大,提出双层隔振的方案来降低井场噪声与振动。首先对双层隔振系统进行数学建模分析,得出双层隔振比单层隔振具有更好的隔振降噪的效果。为验证双层隔振比单层隔振效果更好,对井场内柴油发电机组进行双层隔振的具体方案实施;并对施工完成后的双层隔振的发电机组进行噪声与振动的现场测试。测试结果表明,柴油发电机组采用双层隔振后,隔振效果比原有的单层隔振措施有一定的提高,噪声最大减小了13.5 dB(A)。研究结果表明VOLVO PENTA柴油发电机组采用双层隔振措施可以降低井场噪声与振动。     

S-rough sets and the discovery of F-hiding knowledge

Singular rough sets (S-rough sets) have three classes of forms: one-directional S-rough sets, dual of one-directional S-rough sets, and two-directional S-rough sets. Dynamic, hereditary, mnemonic, and hiding properties are the basic characteristics of S-rough sets. By using the S-rough sets, the concepts of f-hiding knowledge, F-hiding knowledge, hiding degree, and hiding dependence degree are given. Then, both the hiding theorem and the hiding dependence theorem of hiding knowledge are proposed. Finally, an application of hiding knowledge is discussed.     

半同胚定理

本文讨论半拓扑空间的半同胚等价定理及其应用。     

局部紧Hausdorff空间上的Fuzzy测度

研究局部紧Hausdorff空间X上的Fuzzy测度的正则性。首先引入X上内(外)正则集,正则集以及正则Fuzzy测度的概念,并给出了Fuzzy测度正则的充要条件和任意两个紧(或紧Gδ)集的正常差内(外)正则的条件。其次证明单调递增的内正则集的并是内正则的,具有有限Fuzzy测度的单调递减的外正则集的交是外正则的。最后在严格单调条件下,证明具有有限Fuzzy测度的有限个两两不交内正则集的并是内正则的以及每一个紧(或紧Gδ)集是外正则的当且仅当每一个有界开集是内正则的。     

关于Farkas引理证明的一点注记

许多关于非线性规划的专著,如[1]、[2]、[3]等,在证明Farkas引理时都蕴含地用到:“有限生成的凸锥(finitely generated convex cone)为闭集”这样一个事实,但都忽略了对此作出证明。本文旨在于非线性规划的内容范围内证明这一重要事实,从而对上述专著中Farkas引理的证明作出补充。     

WEKA环境下基于模糊理论的聚类算法

因特网上的数据规模大、动态性强,通常发现的知识或规则很可能是不精确和不完备的。为了克服以上不足,引入模糊理论,通过寻找模糊相似上近似集进行合理聚类,在确定聚类数目的过程中,利用平均信息熵进行最佳聚类。同时将模糊聚类算法嵌入WEKA平台,利用WEKA中的类和可视化功能,扩充了WEKA中的聚类算法。实验表明,算法对含有噪声的、分布不规则的大数据集具有很高的精度和收敛速度。     

Seeking Allies: Modelling How Listeners Choose Their Musical Friends

In this paper we describe in some detail a formal computer model of inferential discourse based on a belief system. The key issue is that a logical model in a computer, based on rational sets, can usefully model a human situation based on irrational sets. The background of this work is explained elsewhere, as is the issue of rational and irrational sets (Billinge and Addis, in: Magnani and Dossena (eds.), Computing, philosophy and cognition, 2004; Stepney et al., Journey: Non-classical philosophy—socially sensitive computing in journeys non-classical computation: A grand challenge for computing research, 2004). The model is based on the Belief System (Addis and Gooding, Proceedings of the AISB’99 Symposium on Scientific Creativity, 1999) and it provides a mechanism for choosing queries based on a range of belief. We explain how it provides a way to update the belief based on query results, thus modelling others’ experience by inference. We also demonstrate that for the same internal experience, different models can be built for different actors.