Generalized ordered weighted averaging operators based methods for MADM in intuitionistic fuzzy set setting

Multiattribute decision making（MADM） problems, in which the weights and ratings of alternatives are expressed with intuitionistic fuzzy（IF） sets, are investigated.Firstly, the relative degrees of membership and the relative degrees of non-membership are formulated as IF sets, the weights and values of alternatives on both qualitative and quantitative attributes may be expressed as IF sets in a unified way.Then a MADM method based on generalized ordered weighted averaging operators is proposed.The proposed method is illustrated with a numerical example.

Approach to obtaining weights of uncertain ordered weighted geometric averaging operator

The ordered weighted geometric averaging（OWGA） operator is extended to accommodate uncertain conditions where all input arguments take the forms of interval numbers. First, a possibility degree formula for the comparison between interval numbers is introduced. It is proved that the introduced formula is equivalent to the existing formulae, and also some desired properties of the possibility degree is presented. Secondly, the uncertain OWGA operator is investigated in which the associated weighting parameters cannot be specified, but value ranges can be obtained and the associated aggregated values of an uncertain OWGA operator are known. A linear objective-programming model is established; by solving this model, the associated weights vector of an uncertain OWGA operator can be determined, and also the estimated aggregated values of the alternatives can be obtained. Then the alternatives can be ranked by the comparison of the estimated aggregated values using the possibility degree formula. Finally, a numerical example is given to show the feasibility and effectiveness of the developed method.

Linear goal programming approach to obtaining the weights of intuitionistic fuzzy ordered weighted averaging operator

The multiple attribute decision making problems are studied, in which the information about attribute weights is partly known and the attribute values take the form of intuitionistic fuzzy numbers. The operational laws of intuitionistic fuzzy numbers are introduced, and the score function and accuracy function are presented to compare the intuitionistic fuzzy numbers. The intuitionistic fuzzy ordered weighted averaging （IFOWA） operator which is an extension of the well-known ordered weighted averaging （OWA） operator is investigated to aggregate the intuitionistic fuzzy information. In order to determine the weights of intuitionistic fuzzy ordered weighted averaging operator, a linear goal programming procedure is proposed for learning the weights from data. Finally, an example is illustrated to verify the effectiveness and practicability of the developed method.

Multi-Criteria Group Decision-Making Method Based on an Improved Single-Valued Neutrosophic Hamacher Weighted Average Operator and Grey Relational Analysis

This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.

Group Decision-Making Model of Renal Cancer Surgery Options Using Entropy Fuzzy Element Aczel-Alsina Weighted Aggregation Operators under the Environment of Fuzzy Multi-Sets

Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.

基于有序加权平均算子和后悔理论的城市洪涝灾害韧性评价

针对城市洪涝灾害韧性评价过程主观性强、未考虑决策者有限理性和后悔规避的心理行为导致评价结果失真的难题,提出基于有序加权平均算子和后悔理论的城市洪涝灾害韧性评价方法。首先,结合韧性城市概念,从抵抗能力、预警能力、适应能力、恢复能力4个维度构建指标体系,利用有序加权平均算子将专家极端决策值分布到权重较低位置,通过组合权重的形式求得指标权重,弱化主观偏好极端评价值对权重的影响;然后,考虑专家决策时后悔心理行为特征,构建效用值矩阵、后悔-欣喜值矩阵和感知效用矩阵,得出城市洪涝灾害韧性评价值;最后,将其运用在河南省洪涝灾害韧性评价中,并将计算结果与其他评价方法得出的结果对比分析。结果表明:4种方法评价结果基本一致,均认为河南省洪涝灾害韧性等级为Ⅲ级,提出的方法评价结果精度更高、更贴近实际情况。此外,各地级市韧性等级差异较大,分布不均,整体呈现西南部城市韧性等级高于东北部城市的特征。

基于博弈论组合赋权-云模型的消防员训练损伤风险评估

为降低消防员训练损伤发生率,从个人因素、环境因素和组织管理因素3个方面,提出包含19个指标的消防员训练损伤风险评估指标体系;采用Bonferroni有序加权平均算子(BON-OWA算子)修正层次分析法(AHP)的误差,获得各指标的主观权重;引用基于指标相关性的权重确定法(CRITIC)确定各指标的客观权重;基于博弈论组合赋权法确定各指标的组合权重;引入云模型理论,建立消防员训练损伤风险评估模型,并以河南省某消防救援大队消防员的训练为例,验证该模型的科学性。结果表明:训练装备的战技性能状况指标对消防员的训练损伤风险等级影响最大;该风险评估模型通过数据处理,可以确定消防员训练损伤风险等级;案例中,消防员在5种不同情景下的训练损伤风险等级均为一般风险,这与模糊综合评价法所得结果一致。

转炉车间火灾风险评估方法的改进及应用

为针对性地解决转炉炼钢作业时的消防安全问题,提出将熵权-最优最劣法(Best Worst Method,BWM)和物元可拓模型相结合的转炉车间火灾风险评估模型。通过将指标分为人、物料设备、环境、管理及消防设施5大类,构建转炉车间火灾风险评估指标体系;利用复合语言对35个指标进行评价,引入有序加权平均算子(Ordered Weighted Averaging,OWA)计算各语言的犹豫语言术语集(Hesitant Fuzzy Linguistic Term Set,HFLTS)模糊包络,再根据各专家权重进行加权计算并将语言量化构成评价矩阵;基于熵权、BWM分别算得各指标权重,再运用最小二乘法得到综合权重;最后利用物元可拓模型确定各指标及转炉车间的火灾风险等级。以河北省某炼钢转炉车间为例进行评估得出:该转炉车间的综合风险等级为I级(安全),其中动火监护的人员监管情况、氧枪法兰松紧度、炉前温度环境、作业现场物品摆放情况、作业巡查及设备检查情况和消防疏散通道堵塞情况仍需改善。

油氢合建站时序性动态风险评估研究

油氢合建站作为新型能源基础设施,在实现传统油品加注和氢燃料运营的过程中面临诸多安全新问题,细致全面的风险评估模型将为油氢合建站安全管理提供重要理论支撑。提出了基于复杂网络分析的油氢合建站时序性动态风险评估模型,并应用于油氢合建站火灾爆炸事故。首先,针对灾害链构建的油氢合建站复杂网络结构特征,绘制事故致因链,探究事故的发生路径和内在致因机制。其次,考虑到不同时段风险发展趋势规律的差异性,引入时序加权平均算子(Time-Ordered Weighted Averaging, TOWA)和时序加权几何平均算子(Time-Ordered Weighted Geometric Averaging, TOWGA),结合季节维度对油氢合建站进行动静态综合评估。该方法能够直观揭示时段差异下,各风险指标对系统整体风险的影响程度,从季节角度为高风险灾害事件的防控提供了一种有益探索。

区域海事事故治理效果动态综合评价

为准确评价区域海事事故治理效果,通过构建动态综合评价模型,为水上交通安全规划提供决策依据。首先,从事故的绝对指标与相对指标角度出发,建立包含8个指标的区域海事事故治理效果评价指标体系。其次,使用博弈赋权法对熵权法所得权重和指标相关性权重确定法(Criteria Importance Through Intercriteria Correlation, CRITIC)所得权重进行组合,以确定各时段评价指标组合权重,并采用逼近理想解排序法(Technique for Order Preference by Similarity to Ideal Solution, TOPSIS)对各地区海事事故治理效果进行各时段静态综合评价。再次,通过混合时序算子集结各时段静态综合评价值,求得各地区海事事故治理效果的动态综合评价值,进而判断各地区海事事故的治理效果。最后,运用所建评价模型对2017—2021年上海、浙江、广东和山东4个地区海事事故治理效果进行动态综合评价。研究结果显示:与单一赋权TOPSIS法相比,博弈赋权-TOPSIS法所得静态综合评价结果更为合理可靠;与单一时序算子相比,混合时序算子所得动态综合评价结果更为合理可靠;随着海事事故治理策略和治理强度不同,上海和广东地区海事事故治理效果呈上升趋势,而浙江和山东地区海事事故治理效果呈下降趋势;广东地区海事事故治理效果稳定性最强,而浙江地区海事事故治理效果稳定性最弱;上海地区海事事故治理效果最好,而浙江地区海事事故治理效果最差。

基于三维空间的新型配电网关键技术时空适应性评估

在新型电力系统发展的背景下,针对配电网规划建设和配电网关键技术在实际应用时与所处时空的适应能力、应用缺陷难定量化等问题,分析新型配电网关键技术的建设条件,提出一种基于电网满足度、时空资源度、成效改善度的三维立体空间的技术时空适应性评估模型.采用连续区间有序加权平均算子对层次分析法主观赋权进行改进,引入标准间冲突性相关性法构建的主客观组合赋权方法,解决了单一赋权法具有偏向性的问题.利用模糊综合评价法确定各指标隶属度,进而得到新型配电网关键技术评价等级.算例结果表明,所提方法能够量化配电网关键技术与所处时空的契合程度和双向辨识关键技术对于不同时空的适应性以及不同时空对于技术应用的满足度,揭示配电网关键技术的薄弱环节,有助于提升配电网投资效率与效益,更好地服务经济社会高质量发展.

“中国天眼”宁静区生态安全格局识别--基于OWA和电路理论

“中国天眼”工程FAST(Five-hundred-meter aperture spherical telescope)是国家重大科技基础设施工程,其半径30km内的宁静区生态脆弱,经济社会发展滞后,面临生态保护与加快发展的双重压力。构建生态安全格局是协调区域经济发展和生态保护矛盾、促进区域可持续发展的重要途径。以FAST宁静区为研究对象,基于2020年生态系统服务功能,采用有序加权平均多准则决策法(Ordered Weighted Averaging,OWA)考虑了7种情景下各生态系统服务之间的权衡关系并识别出最适合的优先保护区作为FAST宁静区的生态源地;基于生态敏感性结果对基本阻力面进行修正得到综合阻力面;运用电路理论提取生态廊道和关键生态节点,构建FAST宁静区生态安全格局。结果表明:(1)FAST宁静区生态系统服务时空差异显著,2020年较2000年生态系统服务平均值降低的类型为水源涵养和土壤保持,增加的类型为固碳和生境质量。(2)识别生态源地数共44个,源地面积197.15 km^(2),呈北密南疏、西多东少的空间分布态势,多集中分布在乡镇之间的交界处。(3)提取了72条活跃廊道和3条非活跃廊道,生态廊道总长度537.66km,廊道总体呈蛛网状分布特征。识别38个生态夹点和18处一级障碍点,面积分别为2.56km^(2)和14km^(2)。(4)基于分析结果和FAST工程安全运行的需要,提出FAST宁静区生态分区管控方案:FAST的核心区、中间区西南部和边远区西北部为生态重要区,中间区北部和边远区南部为生态改善区,其余为一般生态区。

基于IOWA算子的空气质量组合预测

对空气质量指数进行预测,反映数据波动的趋势与规律,提出基于诱导有序加权平均(IOWA)算子的Prophet-EEMD-XGBoost模型。首先利用Prophet算法将数据分解为趋势项、季节项、节假日、误差项;然后集合经验模态分解EEMD将原始数据分为9项IMF以及残余分量。最后,利用XGBoost模型对各分量分别进行预测,预测结果利用MAE、MAPE、RMSE、RMSPE进行评价。结果表明,相较于一些单预测模型与其他组合预测模型,基于IOWA算子的Prophet-EEMD-XGBoost组合预测模型有更好的预测效果。

基于OWA算子的模糊n-cell数排序方法

针对基于模糊n-cell数的多属性排序问题,提出了一种基于有序加权平均算子(OWA算子)的模糊n-cell数排序方法。该方法首先根据样本数据对评估对象的属性构造模糊n-cell数,其次根据均值将属性按照从大到小排列,然后选取合适的权重向量,应用OWA算子进行信息聚合得到综合模糊n-cell数,接着根据各分量均值得到排序结果。最后,将该方法运用到实例中,并与传统的均值方法进行了比较。结果表明该方法不仅灵活有效,可根据具体情况选择不同的OWA权重来消除部分不合理的情况,使结果更有说服力,还弥补了传统均值方法的不足。

基于QAR数据的飞行员个体超限风险精细化评价模型

为定量评价飞行员个体超限风险,提出一种基于快速存取记录器(QAR)数据和飞行品质监控(FOQA)的飞行员个体超限风险精细化评价模型。首先,根据事故统计结果、国际民航组织(ICAO)及FOQA基站划分的核心风险类别,选取其中3类风险的FOQA监控项目作为评价指标,计算飞行员个体单项核心风险值;然后,运用熵权逼近理想解排序法(TOPSIS)测算各项核心风险值所占权重,提出飞行员个体超限风险精细化评价模型;最后,将模型运用于实际飞行风险量化评价,通过采集中国民航(CAAC)FOQA基站中共9317条多源融合数据,量化飞行员个体超限风险,得到飞行员个体超限风险量化值排序,结合K-means聚类算法划分飞行员个体超限风险等级。结果表明:该模型可量化排序1693名飞行员个体超限风险,并将飞行员超限风险等级划分为高风险、中风险和低风险3类。

分数阶频率加权能量算子在滚动轴承故障诊断中的应用

针对强噪声背景下滚动轴承故障特征难以提取的问题,提出了一种新的特征增强方法——分数阶频率加权能量算子。首先,利用傅里叶变换将信号从时域转换到频域,得到信号频谱的幅值函数和相位函数;其次,设定微分阶次的变化范围和变化步长,根据傅里叶变换的时域微分性质在频域内对信号的幅值函数进行分数阶微分处理,将微分处理后的幅值函数与相位函数相结合,再利用傅里叶反变换得到微分处理后的信号;最后,对不同阶次的微分信号进行Hilbert变换得到包络信号,利用包络峭度指标选择最佳的微分阶次,利用该阶次下的微分信号求取包络谱,从而确定轴承的故障模式。实验结果表明,该方法可以有效地提取出强噪声背景下的滚动轴承故障特征。

建筑工程中基于层次分析和综合权重的施工质量分析方法

针对传统的质量管理方法往往难以全面而准确地评估施工过程中的各项因素的问题,提出了一种基于层次分析和综合权重的施工质量控制方法,并进行了研究设计,包括指标体系构建、递阶层次结构的建立、指标分析,从而对整个施工过程进行质量把控。

轮轨激扰下高速动车组轴箱轴承故障特征解调方法研究

针对希尔伯特变换无法在轮轨激扰下实现轴箱轴承故障信息识别的缺陷,提出使用高阶频率加权能量算子(High-Order Frequency-Weighted Energy Operator,HFWEO)对轴箱轴承故障冲击进行识别的新方法。首先,通过高速动车组单轴滚动振动试验台进行了轮轨激扰下轴箱振动信号的采集,并对轴箱振动特性进行了分析,得出轮对踏面损伤产生的轮轨激扰主要位于1 kHz以下的低频部分,而轴承故障冲击主要位于1 kHz以上高频的部分;然后,通过公式推导分析了HFWEO的解调特性,并讨论了HFWEO的信号干扰比(Signal-to-Interference Ratio,SIR)随HFWEO阶次变化的规律,证明高阶频率加权能量算子可在轮轨激扰下实现轴箱轴承的故障诊断;最后,将HFWEO应用于轮轨激扰下的轴箱轴承故障数据分析,验证了HFWEO解调方法的有效性与优越性。

Interval-valued intuitionistic fuzzy aggregation operators

The notion of the interval-valued intuitionistic fuzzy set （IVIFS） is a generalization of that of the Atanassov＇s intuitionistic fuzzy set. The fundamental characteristic of IVIFS is that the values of its membership function and non-membership function are intervals rather than exact numbers. There are various averaging operators defined for IVlFSs. These operators are not monotone with respect to the total order of IVIFS, which is undesirable. This paper shows how such averaging operators can be represented by using additive generators of the product triangular norm, which simplifies and extends the existing constructions. Moreover, two new aggregation operators based on the t.ukasiewicz triangular norm are proposed, which are monotone with respect to the total order of IVIFS. Finally, an application of the interval-valued intuitionistic fuzzy weighted averaging operator is given to multiple criteria decision making.

The Average Errors for Linear Combinations of Bernstein Operators on the Wiener Space

In this paper, we discuss the average errors of function approximation by linear combinations of Bernstein operators. The strongly asymptotic orders for the average errors of the combinations of Bernstein operators sequence are determined on the Wiener space.