Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

A MULTI-ATTRIBUTE LARGE GROUP EMERGENCY DECISION MAKING METHOD BASED ON GROUP PREFERENCE CONSISTENCY OF GENERALIZED INTERVAL-VALUED TRAPEZOIDAL FUZZY NUMBERS

In this paper, a new decision making approach is proposed for the multi-attribute large group emergency decision-making problem that attribute weights are unknown and expert preference information is expressed by generalized interval-valued trapezoidal fuzzy numbers （GITFNs）. Firstly, a degree of similarity formula between GITFNs is presented. Secondly, expert preference information on different alternatives is clustered into several aggregations via the fuzzy clustering method. As the clustering proceeds, an index of group preference consistency is introduced to ensure the clustering effect, and then the group preference information on different alternatives is obtained. Thirdly, the TOPSIS method is used to rank the alternatives. Finally, an example is taken to show the feasibility and effectiveness of this approach. These method can ensure the consistency degree of group preference, thus decision efficiency of emergency response activities can be improved.

Novel combinatorial algorithm for the problems of fuzzy grey multi-attribute group decision making

To study the fuzzy and grey information in the problems of multi-attribute group decision making, the basic concepts of both fuzzy grey numbers and grey interval numbers are given firstly, then a new model of fuzzy grey multi-attribute group decision making based on the theories of fuzzy mathematics and grey system is presented. Furthermore, the grey interval relative degree and deviation degree is defined, and both the optimistic algorithm of the grey interval relational degree and the algorithm of deviation degree minimization for solving this new model are also given. Finally, a decision making example to demonstrate the feasibility and rationality of this new method is given, and the results by using these two algorithms are uniform.

Similar simulation study on the deformation and failure of surrounding rock of a large section chamber group under dynamic loading

Large and super-large section chamber groups in coal mines are frequently affected by dynamic loads resulting from production activities such as roadway driving and blasting.The stability of the surrounding rock is poor,and it is difficult to control.In this paper,a similar simulation test was used to study the deformation and evolution laws of the surrounding rock of a triangle-shaped chamber group under different dynamic loads.The results showed that under dynamic loading,the vertical stress of the surrounding rock of the chamber group increased in an oscillatory form.The maximum stress concentration coefficient reached 4.09.The damage degree of the roof was greater than that of the two sides.The deformation of the roof was approximately 1.2 times that of the two sides.For the chamber closer to the power source,the stress oscillation amplitude of the surrounding rock was larger,and the failure was more serious.The force of the anchorage structure showed a phased increasing characteristic;additionally,the force of the anchorage structure on the adjacent side of the chambers was greater than that on the other side.This study reveals the deformation and failure evolution laws of the surrounding rock of large section chamber groups under dynamic loading.

Power Aggregation Operators of Simplified Neutrosophic Sets and Their Use in Multi-attribute Group Decision Making

The simplified neutrosophic set(SNS) is a useful generalization of the fuzzy set that is designed for some practical situations in which each element has different truth membership function, indeterminacy membership function and falsity membership function. In this paper, we develop a series of power aggregation operators called simplified neutrosophic number power weighted averaging(SNNPWA) operator, simplified neutrosophic number power weighted geometric(SNNPWG) operator, simplified neutrosophic number power ordered weighted averaging(SNNPOWA) operator and simplified neutrosophic number power ordered weighted geometric(SNNPOWG) operator. We present some useful properties of the operators and discuss the relationships among them. Moreover, an approach to multiattribute group decision making(MAGDM) within the framework of SNSs is developed by the above aggregation operators.Finally, a practical application of the developed approach to deal with the problem of investment is given, and the result shows that our approach is reasonable and effective in dealing with uncertain decision making problems.

Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making

Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multiattribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean(PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable(PULV) and explore some properties of the operator.Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.

Multi-attribute group decision making method under 2-dimension uncertain linguistic variables

A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.

Fuzzy interval linguistic sets with applications in multi-attribute group decision making

Uncertain and hesitant information, widely existing in the real-world qualitative decision making problems, brings great challenges to decision makers. Hesitant fuzzy linguistic term sets(HFLTSs), an effective linguistic computational tool in modeling and eliciting such information, have hence aroused many scholars’ interests and some extensions have been introduced recently.However, these methods are based on the discrete linguistic term framework with the limited expression domain, which actually depict qualitative information using several single values. Therefore,it is hard to ensure the integrity of the semantics representation and the accuracy of the computation results. To deal with this problem, a semantics basis framework called complete linguistic term set(CLTS) is designed, which adopts a separation structure of linguistic scale and expression domain, enriching semantics representation of decision makers. On this basis the concept of fuzzy interval linguistic sets(FILSs) is put forward that employs the interval linguistic term with probability to increase the flexibility of eliciting and representing uncertain and hesitant qualitative information. For practical applications, a fuzzy interval linguistic technique for order preference by similarity to ideal solution(FILTOPSIS) method is developed to deal with multi-attribute group decision making(MAGDM) problems. Through the cases of movie and enterprise resource planning(ERP) system selection, the effectiveness and validity of the proposed method are illustrated.

Cells grouping scheme against pilot contamination in large scale antennas system

The influence of cells groupings factor to the performance of the cells groupings time-shift pilot scheme is researched for the multiple cells large scale antennas systems（LSAS）. The former researches have confirmed that the cells groupings time-shift pilots scheme is effective to reduce inter-cell interference, especially pilot contamination, which results from the pilot reuse in adjacent cells. However, they have not specified reasonable cells groupings factor, which plays a critical role in the general performance of the LSAS. Therefore, this problem is researched in details. The time for reverse-link data transmission will be compressed, when the groupings factor surpasses a certain range. Thus it is not always beneficial to increase the cells groupings factor without limitation. Furthermore,a reasonable cells groupings factor is deduced from the perspective of optimization to enhance the system performance. Simulations verify the proposed cell grouping factor.

Five Large Generation Groups: Competing in Capital Operation

Since the reform of electric power industry in 2002, the newly established five large generation groups have been persisting in the development strategy of "taking electricity as the core and extending to up-and-downstream businesses." Stringent measures were taken in capital operation and their potential has been shown through electric power as- sets acquiring, coal and financial resources investing, capital market financing as well as power utility restructuring. The five groups are playing more and more important roles in merger and acquisition (M&A) and capital markets.

Clustering Analysis of Black-start Decision-making with a Large Group of Decision-makers

The optimization of black-start decision-making plays an important role in the rapid restoration of a power system after a major failure/outage.With the introduction of the concept of smart grids and the development of real-time communication networks,the black-start decision-makers are no longer limited to only one or a few power system experts such as dispatchers,but rather a large group of professional people in practice.The overall behaviors of a large decision-making group of decision-makers/experts are more complicated and unpredictable.However,the existing methods for black-start decision-making cannot handle the situations with a large group of decision-makers.Given this background,a clustering algorithm is presented to optimize the black-start decision-making problem with a large group of decision-makers.Group decision-making preferences are obtained by clustering analysis,and the final black-start decision-making results are achieved by combining the weights of black-start indexes and the preferences of the decision-making group.The effectiveness of the proposed method is validated by a practical case.This work extends the black-start decision-making problem to situations with a large group of decision-makers.

Two-Edge-Corner Image Features for Registration of Geospatial Images with Large View Variations

This paper presents a robust image feature that can be used to automatically establish match correspondences between aerial images of suburban areas with large view variations. Unlike most commonly used invariant image features, this feature is view variant. The geometrical structure of the feature allows predicting its visual appearance according to the observer’s view. This feature is named 2EC (2 Edges and a Corner) as it utilizes two line segments or edges and their intersection or corner. These lines are constrained to correspond to the boundaries of rooftops. The description of each feature includes the two edges’ length, their intersection, orientation, and the image patch surrounded by a parallelogram that is constructed with the two edges. Potential match candidates are obtained by comparing features, while accounting for the geometrical changes that are expected due to large view variation. Once the putative matches are obtained, the outliers are filtered out using a projective matrix optimization method. Based on the results of the optimization process, a second round of matching is conducted within a more confined search space that leads to a more accurate match establishment. We demonstrate how establishing match correspondences using these features lead to computing more accurate camera parameters and fundamental matrix and therefore more accurate image registration and 3D reconstruction.

Recent Advances in Particle Swarm Optimization for Large Scale Problems

Accompanied by the advent of current big data ages,the scales of real world optimization problems with many decisive design variables are becoming much larger.Up to date,how to develop new optimization algorithms for these large scale problems and how to expand the scalability of existing optimization algorithms have posed further challenges in the domain of bio-inspired computation.So addressing these complex large scale problems to produce truly useful results is one of the presently hottest topics.As a branch of the swarm intelligence based algorithms,particle swarm optimization (PSO) for coping with large scale problems and its expansively diverse applications have been in rapid development over the last decade years.This reviewpaper mainly presents its recent achievements and trends,and also highlights the existing unsolved challenging problems and key issues with a huge impact in order to encourage further more research in both large scale PSO theories and their applications in the forthcoming years.

装备制造行业大型企业集团总部层级事故隐患管控架构研究

为了提升装备制造行业大型企业集团对下属企业事故的隐患管理能力,需要以信息化、数字化手段实现集团级管控能力建设。在“工业互联网体系架构2.0”的基础上,以匹配实际生产流程、人机环全要素管理、覆盖多层级组织层级为目标,构建“工业互联网+大型企业集团总部事故隐患管控”的数字化管控方案,对该架构所需功能模块进行了研究,并提出了管控过程中态势感知与绩效评价的多层级管控循环。本研究提出的数字化管控模式,可有效提升集团总部对所属企业事故隐患管控的全面性、准确性与有效性,可推动对事故隐患告警的数字化、智能化管控水平。

基于信息熵及专家群决策的大型制冷设备耗电量主动复合控制方法

针对大型制冷设备耗电量主动复合控制方法响应速度过慢的问题,设计了大型制冷设备耗电量主动复合控制方法。分析大型制冷设备在不同状态下的耗电量情况,构建大型制冷设备耗电量模型;定义耗电量输出数据的信息熵,确定控制系统的输出指标以及设备的变化参数;结合专家群决策与隶属函数,分析制冷设备耗电量控制的动态误差与控制精度之间的关系,设计复合控制算法;考虑控制方法稳态误差,设置控制规则,实现对大型制冷设备耗电量的主动复合控制。实验结果表明,所设计方法的响应时间为20 ms,响应速度更快,在实际应用中具有较好的应用效果和应用性能。

近距离煤层群采空区下切眼掘进及支护技术研究

为确保近距离煤层群开采下部工作面切眼安全掘进,以5303采煤工作面切眼为研究对象,结合现场情况针对性提出切眼掘进及支护安全技术,并进行工程应用。在5303采煤工作面切眼掘进期间,通过层间距(切眼与上覆采空区间)持续探测、切眼顶板注浆及分次掘进方式确保大断面切眼掘进安全;通过锚网索、单体+工字钢架棚方式维护大跨度切眼围岩稳定。工程应用后,5303采煤工作面切眼得以安全高效掘进,切眼围岩变形量较小,表明现场采用的掘进及支护技术可满足近距离采空区下大跨度切眼施工需要。

Grouping response method for equivalent static wind loads based on a modified LRC method

Wind loading is one of the most important loads for controlling the design of large-span roof structures. Equivalent static wind loads, which can generally aim at determining a specific response, are widely used by structural designers. A method for equivalent static wind loads applicable to multi-responses is proposed in this paper. A modified load- response-correlation （LRC） method corresponding to a particular peak response is presented, and the similarity algorithm implemented for the group response is described. The main idea of the algorithm is that two responses can be put into one group if the value of one response is close to that of the other response, when the structure is subjected to equivalent static wind loads aiming at the other response. Based on the modified LRC, the grouping response method is put forward to construct equivalent static wind loading. This technique can simultaneously reproduce peak responses for some grouped responses. To verify its computational accuracy, the method is applied to an actual large-span roof structure. Calculation results show that when the similarity of responses in the same group is high, equivalent static wind loads with high accuracy and reasonable magnitude of equivalent static wind distribution can be achieved.

Platinum-Group Element Geochemical Characteristics of the Picrites and High-Ti Basalts in the Binchuan Area,Yunnan Province

The Binchuan area of Yunnan is located in the western part of the Emeishan large igneous province in the western margin of the Yangtze Block. In the present study, the Wuguiqing profile in thickness of about 1440 m is mainly composed of high-Ti basalts, with minor picrites in the lower part and andesites, trachytes, and rhyolites in the upper part. The picrites have relatively higher platinum- group element （PGE） contents （PGE=16.3-28.2 ppb）, with high Cu/Zr and Pd/Zr ratios, and low S contents （5.03-16.9 ppm）, indicating the parental magma is S-unsaturated and generated by high degree of partial melting of the Emeishan large igneous province （ELIP） mantle source. The slightly high Cu/Pd ratios （11 000-24 000） relative to that of the primitive mantle suggest that 0.007% sulfides have been retained in the mantle source. The PGE contents of the high-Ti basalts exhibit a wider range （~PGE=0.517-30.8 ppb）. The samples in the middle and upper parts are depleted in PGE and have ~Nd （260 Ma） ratios ranging from -2.8 to -2.2, suggesting that crustal contamination of the parental magma during ascent triggered sulfur saturation and segregation of about 0.446%-0.554% sulfides, and the sulfide segregation process may also provide the ore-forming material for the magmatic Cu-Ni-PGE sulfide deposits close to the studied basalts. The samples in this area show Pt- Pd type primitive mantle-normalized PGE patterns, and the Pd/Ir ratios are higher than that of the primitive mantle （Pd/Ir=l）, indicating that the obvious differentiation between Ir-group platinum- group elements （IPGE） and Pd-group platinum-group elements （PPGE） are mainly controlled by olivine or chromites fractionation during magma evolution. The Pd/Pt ratios of most samples are higher than the average ratio of mantle （Pd/Pt=0.55）, showing that the differentiation happened between Pt and Pd. The differentiation in picrites may be relevant to Pt hosted in discrete refractory Pt-alloy phase in the mantle; whereas the differentiation in the high-Ti basalts is probably associated with the fractionation of Fe-Pt alloys, coprecipitating with Ir-Ru-Os alloys. Some high-Ti basalt samples exhibit negative Ru anomalies, possibly due to removal of laurite collected by the early crystallized chromites.

Behavior of Pile Group with Elevated Cap Subjected to Cyclic Lateral Loads

The pile group with elevated cap is widely used as foundation of offshore structures such as turbines, power transmission towers and bridge piers, and understanding its behavior under cyclic lateral loads induced by waves, tide water and winds, is of great importance to designing. A large-scale model test on 3×3 pile group with elevated cap subjected to cyclic lateral loads was performed in saturated silts. The preparation and implementation of the test is presented. Steel pipes with the outer diameter of 114 mm, thickness of 4.5 mm, and length of 6 m were employed as model piles. The pile group was cyclic loaded in a multi-stage sequence with the lateral displacement controlled. In addition, a single pile test was also conducted at the same site for comparison. The displacement of the pile cap, the internal forces of individual piles, and the horizontal stiffness of the pile group are presented and discussed in detail. The results indicate that the lateral cyclic loads have a greater impact on pile group than that on a single pile, and give rise to the significant plastic strain in the soil around piles. The lateral loads carried by each row of piles within the group would be redistributed with loading cycles. The lateral stiffness of the pile group decreases gradually with cycles and broadly presents three different degradation patterns in the test. Significant axial forces were measured out in some piles within the group, owing to the strong restraint provided by the cap, and finally lead to a large settlement of the pile group. These findings can be referred for foundation designing of offshore structures.

基于社交媒体数据的应急决策大群体群智知识挖掘及其价值测度方法研究

本文针对突发事件下的社交媒体数据体量庞大,但能够辅助应急决策的大群体群智知识分布无序且价值难以测度的问题,提出了一种应急决策大群体群智知识挖掘及其价值测度方法。首先,基于社交媒体博文数据,依据特定应急决策知识框架,采用TF-IDF(term frequency-inverse document trequency)法和改进后的词汇链算法构建了应急决策大群体群智知识挖掘方法;然后,提出了博文热度计算方法,在此基础上根据知识的语义重要性计算博文包含的群智知识总价值,并使用Shapley函数对群智知识价值进行分配;最后,以“新冠疫情”事件为案例对方法进行应用,并通过对比分析说明了方法的有效性和优越性。