相容粗糙集在音频检索中的应用

针对数字技术的发展促使个人的多媒体数据资料量越来越大,给人们的使用造成很大的不便,人们迫切需要能对这些资料进行检索和管理的工具,提出了利用相容粗糙集理论对音频数据进行预检索的新方法,即在相容类的近似空间中对音频数据进行预检索.实验结果表明,该方法可以有效地克服等价粗糙集在音频检索方面的限制,对提高检索效率具有一定的作用.     

测试代价敏感的粗糙集方法

在粗糙集模型中,α量化不可分辨关系是强与弱不可分辨关系的推广形式.然而值得注意的是,基于这三种不可分辨关系的粗糙集并未考虑数据中属性的测试代价.为解决这一问题,提出了测试代价敏感的α量化粗糙集模型,从二元关系的角度使得粗糙集模型代价敏感,并将新模型与基于强不可分辨、弱不可分辨以及传统α量化不可分辨关系的粗糙集模型进行了对比分析.进一步地,通过分析传统启发式算法在求解约简的过程中未考虑降低代价这一不足之处,提出一种新的属性适应性函数,并将其应用于基于遗传算法的约简求解中.实验结果表明该方法不仅可以降低由边界域所带来的不确定性而且同时降低了约简后的测试代价.     

基于粗糙集和证据理论的决策规则提取

提出一种基于粗糙集和证据理论的两阶段决策规则提取算法, 该算法首先利用粗糙集中属性缩减的思想, 找出每条规则中的重要条件属性集合, 然后再基于证据理论中证据结合的思想进一步去掉重要条件属性集中的冗余条件属性, 从而得到最终的决策规则. 所给算法简化了属性集的约简, 对高维数据也是可行的. 实验结果表明, 利用该算法能够挖掘出高质量的决策规则.     

Simulated annealing algorithm for the optimal translation sequence of the jth agent in rough communication

In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.     

模糊信息系统知识约简的分辨函数法

知识约简是粗糙集理论的重要研究内容.针对不同的粗糙集模型和约简定义,给出相应的知识约简方法一直是知识约简的主要任务.以分辩函数法为代表的各种符号值信息系统知识约简方法已得到深入研究.将分辨函数引入模糊信息系统,得到相应的知识约简分辨函数法,并通过实例分析说明了该方法的具体计算步骤.这为从模糊信息系统中获取知识提供了一种有效的粗糙集方法.     

模具粗加工的自适应层切算法仿真研究

分析了基于层切法的零件模具数控粗加工方法,提出了以层面间台阶最大差值为自适应参量的自适应模具数控粗加工方法;对约束条件进行了详细说明,阐述了自适应层切方法的具体步骤及算法流程图。利用已开发的层切法仿真软件平台,进行了三维模型层切法实例仿真分析。分析结果表明,应用该方法可以进一步减少层切法粗加工残留材料体积,对提高层切法模具数控粗加工效率具有实际意义。     

Rough function model and rough membership function

Two pairs of approximation operators, which are the scale lower and upper approximations as well as the real line lower and upper approximations, are defined. Their properties and antithesis characteristics are analyzed. The rough function model is generalized based on rough set theory, and the scheme of rough function theory is made more distinct and complete. Therefore, the transformation of the real function analysis from real line to scale is achieved. A series of basic concepts in rough function model including rough numbers, rough intervals, and rough membership functions are defined in the new scheme of the rough function model. Operating properties of rough intervals similar to rough sets are obtained. The relationship of rough inclusion and rough equality of rough intervals is defined by two kinds of tools, known as the lower （upper） approximation operator in real numbers domain and rough membership functions. Their relative properties are analyzed and proved strictly, which provides necessary theoretical foundation and technical support for the further discussion of properties and practical application of the rough function model.     

Designing a Hybrid Intelligent Mining System for Credit Risk Evaluation

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.     

基于Rough集理论的同类人员综合评判模型及其简化

基于 Rough集理论 ,通过建立同类人员评判模型 ,利用此模型及其简化模型的算法 ,探索以可达到高效率评判各类人员中同类人员为目的的技术和方法 ,并以实例加以说明.     

一种基于Rough集的时间序列数据挖掘策略

阐述了基于 Rough集的时间序列数据的挖掘策略 ,重点讨论了时间序列数据中的时序与非时序信息的获取问题 .实践证明 ,Rough集理论作为一种处理模糊和不确定性问题的有效工具 ,对于时间序列数据的挖掘同样也是有效的 .文章强调了时间序列数据中的多方面信息 ,包括原始数据及其变化量、变化率所提供的信息.