Multi-attribute decision making method for air target threat evaluation based on intuitionistic fuzzy sets

The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set （IFS） is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.

Cartesian product over interval valued intuitionistic fuzzy sets

The intuitionistic fuzzy set(IFS) based on fuzzy theory,which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to the interval valued intuitionistic fuzzy set(IVIFS). On the basis of fuzzy set(FS), the IFS is a generalization concept. And the IFS is generalized to the IVIFS.In this paper, the definition of the sixth Cartesian product over IVIFSs is first introduced and its some properties are explored.We prove some equalities based on the operation and the relation over IVIFSs. Finally, we present one geometric interpretation and a numerical example of the sixth Cartesian product over IVIFSs.

Anomaly Detection of Complex Networks Based on Intuitionistic Fuzzy Set Ensemble

Ensemble learning for anomaly detection of data structured into a complex network has been barely studied due to the inconsistent performance of complex network characteristics and the lack of inherent objective function. We propose the intuitionistic fuzzy set（IFS）-based anomaly detection, a new two-phase ensemble method for anomaly detection based on IFS, and apply it to the abnormal behavior detection problem in temporal complex networks.Firstly, it constructs the IFS of a single network characteristic, which quantifies the degree of membership,non-membership and hesitation of each network characteristic to the defined linguistic variables so that makes the unuseful or noise characteristics become part of the detection. To build an objective intuitionistic fuzzy relationship, we propose a Gaussian distribution-based membership function which gives a variable hesitation degree. Then, for the fuzzification of multiple network characteristics, the intuitionistic fuzzy weighted geometric operator is adopted to fuse multiple IFSs and to avoid the inconsistence of multiple characteristics. Finally, the score function and precision function are used to sort the fused IFS. Finally, we carry out extensive experiments on several complex network datasets for anomaly detection, and the results demonstrate the superiority of our method to state-of-the-art approaches, validating the effectiveness of our method.

基于DST-IFS的空中目标敌我属性综合识别

为了实现复杂战场环境下空中目标敌我属性的综合识别,在利用证据权重衡量信息可信度的基础上,提出了一种基于DS证据理论和直觉模糊集相结合(Dempster-Shafer evidence theory-intuitionistic fuzzy sets,DST-IFS)的综合敌我识别方法。首先,分析了空中目标综合敌我识别问题,给出了具体的识别流程;然后,针对DS(DempsterShafer)函数向直觉模糊集转化过程中存在增大信息不确定性的问题,提出了一种信度分配方法用于直觉模糊隶属度和非隶属度赋值,并利用算例验证了信度分配方法的适应性和有效性;接着,给出了基于理想点法(technique for order preference by similarity to ideal solution,TOPSIS)的DST-IFS决策方法步骤;在此基础上,提出了一种基于DST-IFS的空中目标综合敌我识别的方法;最后进行了实例分析,验证了该综合敌我识别方法的有效性。

基于IFS和IPSO算法的干扰资源分配方法

针对多干扰系统同时干扰多部雷达的干扰资源分配问题,提出一种基于直觉模糊集(IFS)和改进粒子群优化(IPSO)算法相结合的干扰资源分配方法。利用己方无源探测系统获得的敌方雷达参数,根据IFS理论得到敌方雷达的威胁系数;整合数据库中战场的己方干扰系统与敌方雷达系统信息,从空域、频域、极化方式和干扰样式4个方面定义了匹配度,表示己方干扰系统对敌方雷达系统的干扰效率,得到匹配度矩阵,结合敌方雷达威胁系数建立干扰目标函数;提出一种自适应调整权重、异步变化学习因子、针对离散问题的IPSO算法,并引入补偿粒子进行盲区搜索,求解出最佳干扰决策。仿真表明,本文提出的干扰资源分配方法相较于传统算法最优解正确率更高,且实时性更好。

IFS-BN结合的辐射源威胁评估方法

针对辐射源威胁评估实时性、复杂性和信息不确定性的问题,将直觉模糊集与贝叶斯网络相结合,提出一种基于IFS-BN的辐射源威胁评估方法。IFS-BN算法通过直觉模糊集刻画贝叶斯网络的节点信息,充分描述节点信息的确定性,不确定性以及犹豫度。同时,将直觉模糊集求得的各辐射源先验概率代入贝叶斯网络模型之中,得出后验概率进行威胁等级排序,并在此基础上建立了相应的评估指标体系。仿真分析表明,算法具有较好的可行性与有效性。与经典贝叶斯网络评估方法相比,IFS-BN算法的结果更加客观合理。

基于IFS交通状态决策信息一致性融合

针对多源交通信息具有模糊性和时变性的特点,引入直觉模糊集理论(IFS),建立多源交通信息一致性融合算法,融合传感器检测信息与人工信息对交通状态进行实时判别.为了解决IFS中非隶属度函数难以确定的问题,借鉴隶属度函数的构造方法,通过建立双隶属度函数构造直觉模糊数.并以直觉模糊数中的隶属度、非隶属度建立支持度函数,量化决策信息的一致性程度,决策信息的支持度越高集成权重越大,并且权值随决策信息的变化而动态更新.最后给出交通状态决策信息融合算法的具体步骤,并通过算例证明算法是有效的.

基于对比平均法的IFS非隶属度函数确定方法

针对直觉模糊集(IFS)非隶属度函数难以确定的问题,提出一种基于对比平均法的IFS非隶属度函数确定方法,给出了详细的算法步骤,并从理论上证明了其正确性。最后,通过实例分析从应用上验证了算法的有效性与实用性。研究表明,该算法可有效地解决元素依属性具有先后顺序特性的一类IFS非隶属度函数确定方法的问题。

基于绝对比较法的IFS非隶属度函数确定方法

直觉模糊集是对Zadeh模糊集最有影响的一种扩充和发展。直觉模糊集非隶属度函数的规范化确定问题,成为制约其应用的一个重要瓶颈。针对直觉模糊集非隶属度函数难以确定的问题,提出一种基于绝对比较法的直觉模糊集非隶属度函数确定方法,给出了详细的算法步骤,并从理论上证明了其正确性。最后,通过实例分析从应用上验证了算法的有效性与实用性。研究表明,该算法可有效地解决元素依属性具有优先特性的一类IFS非隶属度函数确定方法的问题。

基于优先关系定序法的IFS非隶属度函数确定方法

针对直觉模糊集(IFS)非隶属度函数难以确定的问题,提出一种基于优先关系定序法的IFS非隶属度函数确定方法,给出了详细的算法步骤,从理论上证明了该算法的正确性,并分析了算法的时间复杂度与适用范围。最后,通过实例分析从应用上验证了算法的有效性与实用性。研究表明,该算法可有效地解决具有依多属性确定优先次序特性的一类IFS非隶属度函数确定方法的问题。

基于AHP与IFS的单件生产模式下制造需求与资源匹配算法

针对复杂大型装备的单件生产模式产品规格繁多、结构复杂且个性化强、工艺变更频繁且难以标准化、工艺编制难度大、加工周期长、对资源能力依赖严重等特点,以及制造服务提供企业在订单阶段难以对客户需求与当前制造能力的匹配度进行正确、快速预判等问题,提出了基于零件特征的单件生产制造需求和制造资源能力模型。引入基于层次分析法与直觉模糊集的特征工序矩阵与设备资源能力矩阵匹配算法,计算零件需求和资源的匹配度,实现订单阶段的用户需求和制造资源的快速匹配,最后通过企业实例验证了该方法的有效性。研究结果有助于提高单件制造企业的订单评估质量,降低接单风险,增强企业的竞争力。

Intuitionistic fuzzy C-means clustering algorithms

Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain data.An intuitionistic fuzzy C-means algorithm to cluster IFSs is developed.In each stage of the intuitionistic fuzzy C-means method the seeds are modified,and for each IFS a membership degree to each of the clusters is estimated.In the end of the algorithm,all the given IFSs are clustered according to the estimated membership degrees.Furthermore,the algorithm is extended for clustering interval-valued intuitionistic fuzzy sets(IVIFSs).Finally,the developed algorithms are illustrated through conducting experiments on both the real-world and simulated data sets.

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.

Temporal evidence combination method for multi-sensor target recognition based on DS theory and IFS

In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this paper proposes a Dempster-Shafer(DS) theory and intuitionistic fuzzy set(IFS) based temporal evidence combination method(DSIFS-TECM). To realize the method,the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value(IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor(RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference.

Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty

Intuitionistic fuzzy preference relation(IFPR) is a suitable technique to express fuzzy preference information by decision makers(DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR,by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly,a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.

电网侧储能项目管理模式选择——基于IFS与TOPSIS灰色关联投影法的实证分析

电网侧储能项目是一类刚刚兴起的工程项目,针对其最佳建设管理模式选择问题,结合电网储能产业发展阶段及项目具体特点构建电网侧储能项目管理模式选择的评价指标体系,在此基础上应用TOPSIS法、灰色关联分析法和矢量投影法3种理论建立基于TOPSIS灰色关联投影法的电网侧储能项目管理模式选择模型,并为避免传统专家评分法确定指标权重引起的客观性欠缺问题引入直觉模糊集(IFS)对每个评价指标进行赋权。以国内某电力消费大省进行实例验证,计算结果与工程实践相符,说明该方法具有有效性和实用性。

基于加权IFS证据合成的多源信息融合方法

为权衡信息融合系统对各条证据的可信程度,提出基于直觉模糊交叉熵的证据折扣方法,用于直觉模糊证据合成规则。并根据确定性理论,对直觉模糊决策中的记分函数进行改进,得到基于确定性因子的记分函数形式,用于直觉模糊证据合成结果判定。最后通过与其他算法的对比实验,验证算法在多传感器目标识别应用中是有效的,且具有较高的计算效率。

Solving Intuitionistic Fuzzy Linear Programming Problem—II

Under non-random uncertainty, a new idea of finding a possibly optimal solution for linear programming problem is examined in this paper. It is an application of the intuitionistic fuzzy set concept within scope of the existing fuzzy optimization. Here, we solve a linear programming problem (LPP) in an intuitionistic fuzzy environment and compare the result with the solution obtained from other existing techniques. In the process, the result of associated fuzzy LPP is also considered for a better understanding.

Intuitionistic Fuzzy Slight Continuity

In this paper,we introduce the notion of intuitionistic fuzzy slightly continuity as a generalizing fuzzy continuity.Basic properties and preservation theorems of intuitionistic fuzzy slightly continuous functions are obtained.

基于IFE动态直觉模糊法的空战目标威胁评估

针对传统空战多目标威胁评估难以与动态作战态势相结合的缺陷和不足,提出了基于直觉模糊熵(intuitionistic fuzzy entropy,IFE)与动态直觉模糊法相结合的空战多目标威胁评估方法。该方法通过直觉模糊集确定目标属性矩阵,采用IFE算法对目标属性赋权;采用泊松分布法处理多时刻态势信息,计算时间序列权重;建立动态直觉模糊空战多目标威胁评估数学模型,并进行了仿真研究。仿真结果表明该算法是合理和有效的。