模糊规划的谐调度与矛盾规则的排除方法

本文给出了模糊规则的谐调度，得到了两个模糊规则有公共解的充分必要条件，提供了模糊规则知识库中矛盾规则的排除方法。     

模糊规则的谐调度与矛盾规则的排除方法

本文给出了模糊规则的谐调度，得到了两个模糊规则有公共解的充分必要条件，提供了模糊规则知识库中矛盾规则的排除方法．     

直觉模糊粗糙推理的规则库完备性研究

针对规则库检验问题,提出了直觉模糊粗糙规则库的完备性检验方法.首先,引入直觉模糊粗糙集的概念,给出了直觉模糊粗糙规则库的完备性定义;其次,针对直觉模糊粗糙规则库的完备性,提出了完备性检验算法,指出如何设计规则库才能满足完备性要求;最后,通过实例验证了算法的合理性和有效性.     

基于高层建筑结构实例库的模糊关联规则的研究与应用

关联规则的挖掘是数据挖掘的重要研究内容之一,文章基于高层建筑结构实例库展开对模糊关联规则的研究:针对某些数值类型的属性值,提出了区间模糊划分法,将它们转化为模糊数据;对Apriori算法和支持度计数方式作一定的改进;并举例说明模糊型关联规则在高层建筑结构实例库中的发现。     

直觉模糊粗糙推理的规则互作用性研究

针对直觉模糊粗糙逻辑(IFRL)推理的规则库检验问题,提出了IFRL规则库的互作用性检验方法.互作用性检验是逻辑规则库检验的一项重要内容,它可以有效地分析出规则间的关系.利用直觉模糊粗糙集(IFRS)及其包含关系的概念,提出了正规IFRS和IFRL规则库的互作用性定义.在此基础上,将直觉模糊逻辑(IFL)的3个定理推广到IFRL领域,并给予了证明.提出的互作用性定义和推广后的3个定理可以作为检验规则间互作用性的方法.     

数据库中的模糊逻辑规则发现

关联规则是数据库中的知识发现（KDD）领域的重要研究课题。模糊关联规则可以用自然语言来表达人类知识,近年来受到KDD研究人员的普遍关注。但是,目前大多数模糊关联规则发现方法仍然沿用经典关联规则发现中常用的支持度和置信度测度。事实上,模糊关联规则可以有不同的解释,而且不同的解释对规则发现方法有很大影响。从逻辑的观点出发,定义了模糊逻辑规则、支持度、蕴含度及其相关概念,提出了模糊逻辑规则发现算法,该算法结合了模糊逻辑概念和Apriori算法,从给定的定量数据库中发现模糊逻辑规则。     

基于模糊子集的土地利用遥感图像模糊规则分类

为了较好地处理遥感图像的不确定性或模糊性,提高分类精度,提出了一种基于模糊子集的土地利用遥感图像模糊规则分类方法。将模糊隶属度函数值对应到特定的模糊子集建立模糊规则条件,由样本建立分类规则库,通过计算分类数据规则条件部分与分类规则库中规则条件部分的模糊贴进度进行土地利用分类。结果表明:与传统的最大似然法分类方法相比,基于模糊规则的分类方法在高模糊性数据分类中显著提高了分类精度,在低模糊性数据分类中也能取得与最大似然法近似的结果。     

模糊Horn子句规则挖掘算法研究

模糊关联规则可以用自然语言来表达人类知识,受到数据挖掘与知识发现研究人员的广泛关注。但是,目前大多数模糊关联规则挖掘方法仍然基于经典关联规则的支持度和可信度测度。从模糊蕴涵的观点出发,定义了模糊Horn子句规则、支持度、蕴涵强度以及相关概念,提出了模糊Horn子句规则挖掘算法。该算法可以分解为3个步骤。首先,将定量数据库转换为模糊数据库。其次,挖掘模糊数据库中所有支持度不小于指定最小支持度阂值的频繁项目集。一旦得到了所有频繁项目集,就可以用一种直接的方法生成所有蕴涵强度不小于指定最小蕴涵强度阂值的模糊Horn子句规则。     

基于子集融合与规则简约的磨矿过程模糊建模

针对选矿厂磨矿生产过程的模糊建模问题,本文提出一种基于模糊集融合和规则简约的模糊建模方法.该方法针对基于数据建立的磨矿过程Takagi-Sugeno模型,采用模糊C均值聚类方法对同一变量下的隶属度函数参数进行聚类,得到对不同工况具有代表性的融合后的隶属度函数,来降低过度拟合的影响.此外,本文根据规则库中的规则权值,对前件相同的冗余规则进行约简,形成最终的离线模糊规则库,有效提高了规则库的泛化能力.为验证本文方法的有效性,分别采用经典数据与实际工业数据进行了实验论证,从精度和泛化能力上体现了本文方法的优势.     

模糊关联规则支持度选择的一种改进

提出一种模糊关联规则支持度的改进定义,这种定义不仅考虑了它的统计特性,而且考虑了模糊模式的模糊性。     

Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP

Failure mode and effects analysis (FMEA) is a widely used engineering technique for designing, identifying and eliminating known and/or potential failures, problems, errors and so on from system, design, process, and/or service before they reach the customer (Stamatis, 1995). In a typical FMEA, for each failure modes, three risk factors; severity (S), occurrence (O), and detectability (D) are evaluated and a risk priority number (RPN) is obtained by multiplying these factors. There are significant efforts which have been made in FMEA literature to overcome the shortcomings of the crisp RPN calculation. In this study a fuzzy approach, allowing experts to use linguistic variables for determining S, O, and D, is considered for FMEA by applying fuzzy ‘technique for order preference by similarity to ideal solution’ (TOPSIS) integrated with fuzzy ‘analytical hierarchy process’ (AHP). The hypothetical case study demonstrated the applicability of the model in FMEA under fuzzy environment.     

Node connectivity and arc connectivity of a fuzzy graph

The fuzzy graph approach is more powerful in cluster analysis than the usual graph - theoretic approach due to its ability to handle the strengths of arcs effectively. The concept of node-strength sequence is introduced and is studied in a complete fuzzy graph. Two new connectivity parameters in fuzzy graphs namely, fuzzy node connectivity (κ) and fuzzy arc connectivity (κ^′) are introduced and obtained the fuzzy analogue of Whitney’s theorem. Fuzzy node cut, fuzzy arc cut and fuzzy bond are defined. Fuzzy bond is a special type of a fuzzy bridge. It is proved that at least one of the end nodes of a fuzzy bond is a fuzzy cutnode. It is shown that κ=κ^′ for a fuzzy tree and it is the minimum of the strengths of its strong arcs. The relationships of the new parameters with already existing vertex and edge connectivity parameters are studied and is shown that the value of all these parameters are equal in a compete fuzzy graph. Also a new clustering technique based on fuzzy arc connectivity is introduced.     

An alternative characterization of fuzzy complement functional

In this short note we propose a novel fuzzy complement functional. This functional is different from other functionals known in the literature. However, it turns out to be an alternative characterization of the well-known negation function. We sincerely thank the anonymous reviewer whose insightful suggestions have significantly improved the paper.     

A generalized model of fuzzy rough sets

The consideration of approximation problem of fuzzy sets in fuzzy information systems results in theory of fuzzy rough sets. This paper focuses on models of generalized fuzzy rough sets, a generalized model of fuzzy rough sets based on general fuzzy relations are studied, properties and algebraic characterization of the model are revealed, and relationships between this model and related models are also discussed.     

模糊数学在企业信息处理中的应用--模糊人事评价及人事安排、岗位培训决策支持系统

本文讨论了模糊数学在企业信息处理中的应用。提出了模糊人事评价体系，以及企业人事安排、企业员工技能培训等方面的模糊决策支持数学模型。     

液位模糊控制系统设计的应用

采用S7—300可编程序控制器设计了一个模糊控制器，将控制器的模糊输出反模糊化后作为实际输出控制调节阀的开度，使中位水箱的液位达到给定值，直接利用控制经验知识使得控制品质达到良好要求。     

基于模糊算法的数据库查询工具的设计

利用SQL进行数据库查询,可以完成复杂条件的数据查询,但是,它只能表示和处理精确数据,无法表达自然语言中的模糊。针对具体人员信息数据库,提出了基于人员年龄、身高与体重的模糊单词、模糊隶属函数、模糊算子的表达式,并提出了模糊SQL语句的自动生成方法。提出并实现的基于模糊算法的人员信息数据库查询工龄,已经应用于暂住人口IC卡管理信息系统,并对其它相关模糊数据库查询具有有较好的参考意义。     

An introduction to vague complemented ordered sets

The purpose of this paper is to introduce a theory of fuzzily defined complement operations on nonempty sets equipped with fuzzily defined ordering relations. Many-valued equivalence relation-based fuzzy ordering relations (also called vague ordering relations) provide a powerful and a comprehensive mathematical modelling of fuzzily defined partial ordering relations. For this reason, starting with a nonempty set X equipped with a many-valued equivalence relation and a vague ordering relation, a fuzzily defined complement operation (called a vague complement operation) on X will be formulated by means of the underling many-valued equivalence relation and vague ordering relation. Because of the fact that the practical implementations of vague complement operations basically depend on their representation properties, a considerable part of this paper is devoted to the representations of vague complement operations. In addition to this, the present paper provides various nontrivial examples for vague complements, and introduces a many-valued logical interpretation of quantum logic as a real application of vague complements.     

基于进化模糊神经网络的频率选择表面设计方法

频率选择表面是一种二维周期阵列结构,能够有效控制电磁波的传输和反射。为了解决传统设计方法参数选择的盲目性和有效性缺陷,提出一种基于进化模糊神经网络算法的设计方法。该方法具有开放的结构,可以在线自适应并不断进化,克服普通神经网络中模型结构和参数难以设置的缺点,同时系统可以进行模糊规则插入和规则提取等。仿真结果表明,该方法具有更高的准确度,能有效地解决频率选择表面设计工作中的一些相关问题。