On Multi-Granulation Rough Sets with Its Applications

Recently,much interest has been given tomulti-granulation rough sets (MGRS), and various types ofMGRSmodelshave been developed from different viewpoints. In this paper, we introduce two techniques for the classificationof MGRS. Firstly, we generate multi-topologies from multi-relations defined in the universe. Hence, a novelapproximation space is established by leveraging the underlying topological structure. The characteristics of thenewly proposed approximation space are discussed.We introduce an algorithmfor the reduction ofmulti-relations.Secondly, a new approach for the classification ofMGRS based on neighborhood concepts is introduced. Finally, areal-life application from medical records is introduced via our approach to the classification of MGRS.

Multi-Granularity Neighborhood Fuzzy Rough Set Model on Two Universes

The two universes multi-granularity fuzzy rough set model is an effective tool for handling uncertainty problems between two domains with the help of binary fuzzy relations. This article applies the idea of neighborhood rough sets to two universes multi-granularity fuzzy rough sets, and discusses the two-universes multi-granularity neighborhood fuzzy rough set model. Firstly, the upper and lower approximation operators are defined in the two universes multi-granularity neighborhood fuzzy rough set model. Secondly, the properties of the upper and lower approximation operators are discussed. Finally, the properties of the two universes multi-granularity neighborhood fuzzy rough set model are verified through case studies.

Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

Attribute Reduction of Neighborhood Rough Set Based on Discernment

For neighborhood rough set attribute reduction algorithms based on dependency degree,a neighborhood computation method incorporating attribute weight values and a neighborhood rough set attribute reduction algorithm using discernment as the heuristic information was proposed.The reduction algorithm comprehensively considers the dependency degree and neighborhood granulation degree of attributes,allowing for a more accurate measurement of the importance degrees of attributes.Example analyses and experimental results demonstrate the feasibility and effectiveness of the algorithm.

Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets

This socialized environment among educated and developed people causes themto focusmore on their appearance and health,which turns them towards medical-related treatments,leading us to discuss anti-aging treatment methods for each age group,particularly for urban people who are interested in this.Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects.Five anti-aging therapies such as microdermabrasion or dermabrasion,laser resurfacing anti-aging skin treatments,chemical peels,dermal fillers for aged skin,and botox injections are considered in this study.Based on the criteria of safety risk,investment cost,customer happiness,and side effects,the optimal alternative is picked.As a result,a NormalWiggly Hesitant Pythagorean Fuzzy Set(NWHPFS)is constructed and used in Multi-Criteria Decision-Making(MCDM)using traditional wavy mathematical approaches.The entropy approach is utilized to determine weight values,and the Normal Wiggly Hesitant Pythagorean-VlseKriterijumska Optimizacija I Kompromisno Resenje(NWHPF-VIKOR)method is utilized to rank alternatives using MCDM methodologies.Sensitivity analysis and comparative analysis were performed to ensure the robustness and reliability of the proposed method.The smart final choice will undoubtedly assist Decision Makers(DM)in making the right judgments,and the MCDM approach will undoubtedly assist individuals in understanding the medicine.

Buckling Optimization of Curved Grid Stiffeners through the Level Set Based Density Method

Stiffened structures have great potential for improvingmechanical performance,and the study of their stability is of great interest.In this paper,the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method,where the shape and cross section(including thickness and width)of the stiffeners can be optimized simultaneously.The grid stiffeners are a combination ofmany single stiffenerswhich are projected by the corresponding level set functions.The thickness and width of each stiffener are designed to be independent variables in the projection applied to each level set function.Besides,the path of each single stiffener is described by the zero iso-contour of the level set function.All the single stiffeners are combined together by using the p-norm method to obtain the stiffener grid.The proposed method is validated by several numerical examples to optimize the critical buckling load factor.

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

Mechanism Study on the Effect of Retarder on Polyurethane Setting Time Based on Molecular Simulation

This study identified castor oil and phosphate ester as effective retarders through setting time,tensile,and flexural tests,and determined their optimal dosages.The mechanism by which phosphate ester affects the setting time of polyurethane was further investigated using molecular dynamics simulations.Fourier transform infrared spectroscopy was also employed to systematically study the physical and chemical interactions between phosphate esters and polyurethane materials.The results demonstrate that a 1%concentration of phosphate ester provides the most effective retarding effect with minimal impact on the strength of polyurethane.When phosphate ester is added to the B component of the two-component polyurethane system,its interaction energy with component A decreases,as do the diffusion coefficient and aggregation degree of component B on the surface of component A.This reduction in interaction slows the setting time.Additionally,the addition of phosphate ester to polyurethane leads to the disappearance or weakening of functional groups,indicating competitive interactions within the phosphate ester components that inhibit the reaction rate.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

Impact of setting distinct target blood glucose levels on endogenous insulin suppression and pharmacodynamics of insulin preparations

BACKGROUND Insulin therapy plays a crucial role in managing diabetes.Regulatory guidelines mandate assessing the pharmacokinetics(PK)and pharmacodynamics(PD)of new insulin formulations with euglycemic clamp techniques before entry into the market.Typically,blood glucose(BG)levels are maintained at 5%below baseline to suppress endogenous insulin secretion in healthy volunteers.However,in scenarios where BG baseline is relatively low,maintaining it at 5%below baseline can increase hypoglycemic risk.Consequently,we adjusted to maintain it at 2.5%below a baseline of<4.00 mmol/L.It remains uncertain whether this adjustment impacts endogenous insulin inhibition or the PD of study insulin.AIM To evaluate and compare the PD and C-peptide status using two different target BG setting methods.METHODS Data came from euglycemic clamp trials assessing the PK/PD of insulin aspart(IAsp)in healthy participants.Target BG was set at 2.5%below baseline for those with a basal BG of<4.00 mmol/L(group A),and at 5%below baseline for others(group B).The area under the curve(AUC)of IAsp(AUC_(IAsp,0-8 h))and GIR from 0 to 8 hours(AUCGIR,0-8 h)was used to characterize the PK and PD of IAsp,respectively.The C-peptide reduction and PK/PD of IAsp were compared between the two groups.RESULTS Out of 135 subjects,15 were assigned to group A and 120 to group B;however,group B exhibited higher basal Cpeptide(1.59±0.36 vs 1.32±0.42 ng/mL,P=0.006).Following propensity score matching to adjust for basal Cpeptide differences,71 subjects(15 in group A and 56 in group B)were analyzed.No significant differences were observed in demographics,IAsp dosage,or clamp quality.Group B showed significantly higher baseline(4.35±0.21 vs 3.91±0.09 mmol/L,P<0.001),target(4.13±0.20 vs 3.81±0.08 mmol/L,P<0.001),and clamped(4.10±0.17 vs 3.80±0.06 mmol/L,P<0.001)BG levels.Both groups exhibited comparable C-peptide suppression(32.5%±10.0%vs 35.6%±12.1%,P=0.370)and similar IAsp activity(AUCGIR,0-8 h:1433±400 vs 1440±397 mg/kg,P=0.952)under nearly equivalent IAsp exposure(AUC_(IAsp,0-8 h):566±51 vs 571±85 ng/mL×h,P=0.840).CONCLUSION Maintaining BG at 2.5%below a baseline of<4.00 mmol/L did not compromise the endogenous insulin suppression nor alter the observed pharmacodynamic effects of the study insulin.

Geochronology and geodynamic setting of the carbonate-hosted Pb-Zn deposits in world-class Sichuan-Yunnan-Guizhou triangle,South China

Unraveling the precise mineralization age is vital to understand the geodynamic setting and ore-forming mechanism of the sediment-hosted Pb-Zn deposit;this has long been a challenge.The Sichuan-Yunnan-Guizhou(SYG)triangle in the southwestern margin of the Yangtze Block is a globally recognized carbonate-hosted Pb-Zn metallogenic province and also an essential part of the South China low-temperature metallogenic domain.This region has>30 million tons(Mt)Zn and Pb resources and shows the enrichment of dispersed metals,such as Ga,Ge,Cd,Se,and Tl.During the past 2 decades,abundant data on mineralization ages of Pb-Zn deposits within the SYG triangle have been documented based on various radioisotopic dating methods,resulting in significant progress in understanding the geodynamic background and ore formation of Pb-Zn deposits hosted in sedimentary rocks at SYG triangle.This paper provides a comprehensive summary of the geochronological results and Pb-Sr isotopic data regarding Pb-Zn deposits in the SYG triangle,which identified two distinct Pb-Zn mineralization periods influencing the dynamic processes associated with the expansion and closure of the Paleo-Tethys Ocean in the western margin of the Yangtze Block.The predominant phase of Pb-Zn mineralization at SYG triangle spanned from the Middle Triassic to Early Jurassic(226-191 Ma),which was intensely correlated with the large-scale basin fluid transport triggered by the closure of the Paleo-Tethys Ocean and Indosinian orogeny.The secondary Pb-Zn mineralization phase occurred during the Late Devonian to Late Carboniferous and was controlled by extensional structures associated with the expansion of the Paleo-Tethys Ocean.Further investigation is necessary to clarify the occurrence and potential factors involved in the Pb-Zn mineralization events during the Late Devonian to Late Carboniferous.

基于Rough Set理论的“数据浓缩”

本文讨论了基于RoushSet（RS）理论数据浓缩的几个问题．首先，介绍了一个基于差别矩阵的属性约简策略，并给出了数据浓缩的测量；然后分析了对UCI机器学习数据库40余个例子的数据浓缩的结果；最后，我们强调了在数据浓缩中例外的重要性，并讨论了不一致数据浓缩．

一种基于Rough Set理论的属性约简及规则提取方法

该文针对RoughSet理论中属性约简和值约简这两个重要问题进行了研究，提出了一种借助于可辨识矩阵（discernibilitymatrix）和数学逻辑运算得到最佳属性约简的新方法．同时，借助该矩阵还可以方便地构造基于RoushSet理论的多变量决策树．另外，对目前广泛采用的一种值约简策略进行了改进，最终使得到的规则进一步简化．

基于Rough Set的加权朴素贝叶斯分类算法

朴素贝叶斯算法是一种简单而高效的分类算法,但其条件独立性假设并不符合客观实际,这在某种程度上影响了它的分类性能。加权朴素贝叶斯是对它的一种扩展。基于Rough Set的属性重要性理论,提出了基于Rough Set的加权朴素贝叶斯分类方法,并分别从代数观、信息观及综合代数观和信息观的角度给出了属性权值的求解方法。通过在UCI数据集上的仿真实验,验证了该方法的有效性。

基于Rough Set的空间数据分类方法

近来 ,数据采掘的研究已从关系型和事务型数据库扩展到空间数据库 .空间数据采掘是一个很有发展前景的领域 ,其中空间数据分类的研究尚处在起步阶段 .该文分析和比较了现有的几个空间数据分类方法的利和弊 ,提出利用 Rough Set的三阶段空间分类过程 .实验结果表明 。

基于AHP与Rough Set的农业节水技术综合评价

由于不同区域自然条件的差异,农业节水技术自身特点及对应用环境条件的要求,导致不同农业节水技术的应用效果存在很大差异,有较大的不确定性,因此,如何筛选合理的评价指标,构建科学、全面的农业节水技术综合评价方法具有十分重要的意义。根据对农业节水技术应用效果的实地调研,应用Delphi法从调查获得的20项评价指标中筛选出了9项农业节水技术综合评价指标。其中节水率、积温和土壤肥力属于生态因子,产投比、劳动力投入和经济投入属于经济因子,可靠性、推广程度和农民认可度为社会因子。基于以上9项指标,构建了农业节水技术综合评价指标体系.综合评价方法(ARM)通过引入经验因子α对应用层次分析法(AHP)和粗糙集(Rough Set)所获得指标权重进行修订,使指标权重更加合理化。同时,分别应用AHP、Rough Set和ARM对甘肃省武威市的地膜覆盖、秸秆覆盖和常规畦田灌溉在大田中的应用效果进行了综合评价。评价结果显示,在对地膜覆盖技术评价中,AHP法过分强调了经济效益的作用(0.44),Rough Set法则强调的是生态效益(0.33)和社会效益(0.32),弱化了经济效益(0.05),ARM修正了以上2种方法的评价结果,获得地膜覆盖的经济效益、生态效益和社会效益,分别为0.36、0.20和0.13。在对秸秆覆盖评价中,与其它两种方法相比,Rough Set法的评价结果存在显著性差异,ARM修正获得的经济效益、生态效益和社会效益,分别为0.09、0.18和0.06。在对常规畦田灌溉评价中,Rough Set法强调了生态效益(0.28),经过修正获得的经济效益、生态效益和社会效益,分别为0.24、0.01和0.13。ARM的评价结果表明,采用地膜覆盖的经济效益最佳;同常规畦田灌溉相比较,地膜覆盖、秸秆覆盖的生态性指数分别比之高0.19和0.17,主要是由于秸秆覆盖具有保墒、增加土壤有机质以及在作物生长后期调节地温的作用,地膜覆盖具有节水、提高苗期土壤温度和促进提前出苗的作用;同秸秆覆盖相比,地膜覆盖和常规畦田灌溉的社会性指数分别高112.12%、18.18%,说明这两种技术在河西半干旱地区具有良好的社会基础。可见,在西北半干旱地区地膜覆盖用于种植玉米的效果最佳,而秸秆覆盖尽管其生态效益较高,但经济效益较低,推广应用存在一定的难度。

基于Rough Set的规则自动抽取设计方案

知识获取是专家系统的重要研究领域,而理论以理论的独特之处成为这一领域的有效工具。文章针对一具体专家系统Rough Set--专家系统在知识获取方面能力的不足,简要介绍其知识表示和知识获取的方法后,提出了一种基于理论的规则自动抽取OTCA-ES--Rough Set的设计方案。

基于Rough set理论的无线传感器网络节点故障诊断

提出了一种无线传感器网络(WSN)节点故障诊断的新方法,首先基于粗糙集理论中改进的可辨识矩阵算法得到故障诊断决策的属性约简;然后通过属性匹配的故障分类算法,建立一套WSN节点故障诊断方法,对WSN节点的各个模块分别进行具体的故障诊断和定位.仿真实验表明,该方法在WSN节点故障诊断时通信代价小、能量消耗低、诊断准确率高,因而具有在能量有限的WSN节点中应用的可能性.

基于Rough Set理论的判断矩阵构造方法

群决策支持系统 (GDSS)是利用信息技术 ,将多个决策者个人对该领域的理解及个人判断能力结合在一起 ,利用结构化决策分析技术 ,对半结构化和非结构化问题进行求解 .层次分析法是对定性问题作定量分析的一种简便而有效的方法 .提出了一种 GDSS环境下判断矩阵构造的新方法 :运用粗集理论 ,利用管理信息系统运行所积累的大量决策数据来分析各决策因素、决策者对决策目标的影响 ,并建立自学习系统 ,从而构造具有完全一致性的综合判断矩阵 .

基于Rough Set和神经网络的CBR快捷检索方法

检索是CBR中的关键技术,直接影响CBR的推理效率和质量,检索出的案例质量的好坏直接影响着案例重用与修改的难易,该文提出先用粗糙集约简理论去除冗余的案例决策表特征,再用BP神经网络模型来实现相似案例检索,这种检索方法不需要定义案例属性之间的相似度,检索速度快。