International Journal of Approximate Reasoning最新文献_第6页

Generalized conjunction and disjunction of two conditional events in the setting of conditional random quantities 条件随机量下两个条件事件的广义合取与析取

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-07-28 DOI: 10.1016/j.ijar.2025.109533

Lydia Castronovo , Giuseppe Sanfilippo

{"title":"Generalized conjunction and disjunction of two conditional events in the setting of conditional random quantities","authors":"Lydia Castronovo , Giuseppe Sanfilippo","doi":"10.1016/j.ijar.2025.109533","DOIUrl":"10.1016/j.ijar.2025.109533","url":null,"abstract":"<div><div>In recent papers, notions of conjunction and disjunction of two conditional events as suitable conditional random quantities, which satisfy basic probabilistic properties, have been deepened in the setting of coherence. In this framework, the conjunction and the disjunction of two conditional events are defined as five-valued objects, among which are the values of the (subjectively) assigned probabilities of the two conditional events. In the present paper we propose a generalization of these structures, where these new objects, instead of depending on the probabilities of the two conditional events, depend on two arbitrary values <span><math><mi>a</mi><mo>,</mo><mi>b</mi></math></span> in the unit interval. We show that they are connected by a generalized version of the De Morgan's law and, by means of a geometrical approach, we compute the lower and upper bounds on these new objects both in the precise and the imprecise case. Moreover, some particular cases, obtained for specific values of <em>a</em> and <em>b</em> or in case of some logical relations, are analyzed. The results of this paper lead to the conclusion that the only objects satisfying all the logical and the probabilistic properties already valid for the operations between events are the ones depending on the probabilities of the two conditional events.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109533"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Triadic data: Representation and reduction 三元数据：表示与约简

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-07-29 DOI: 10.1016/j.ijar.2025.109532

Léa Aubin Kouankam Djouohou , Blaise Blériot Koguep Njionou , Leonard Kwuida

引用次数: 0

Distribution assessment-based multiple over-sampling with evidence fusion for imbalanced data classification 基于分布评估的多重过采样与证据融合的不平衡数据分类

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-08-06 DOI: 10.1016/j.ijar.2025.109538

Hongpeng Tian , Zuowei Zhang , Zhunga Liu , Jingwei Zuo , Caixing Yang

{"title":"Distribution assessment-based multiple over-sampling with evidence fusion for imbalanced data classification","authors":"Hongpeng Tian , Zuowei Zhang , Zhunga Liu , Jingwei Zuo , Caixing Yang","doi":"10.1016/j.ijar.2025.109538","DOIUrl":"10.1016/j.ijar.2025.109538","url":null,"abstract":"<div><div>Over-sampling methods concentrate on creating balanced samples and have proven successful in classifying imbalanced data. However, current over-sampling methods fail to consider the uncertainty of produced samples, potentially altering the data distribution and impacting the classification process. To address this issue, we propose a distribution assessment-based multiple over-sampling (DAMO) method for classifying imbalanced data. We first introduce a multiple over-sampling method based on distribution assessment to create different forms of synthetic samples. The core is quantifying the inconsistency of data distribution before and after sampling as a constraint to guide multiple over-sampling, thereby minimizing the data shift and characterizing the uncertainty of produced samples. Then, we quantify the local reliability of the classification results and select several imprecise samples with low local reliability that are indistinguishable between classes. Neighbors serve as additional complementary information to calibrate the results of imprecise samples, thereby reducing the likelihood of misclassification. The calibrated results are combined by the discounting Dempster-Shafer fusion rule to make a final decision. DAMO's efficiency has been demonstrated through comparisons with related methods on various real imbalanced datasets.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109538"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel framework for trust network analysis: Connectivity-based intuitionistic fuzzy rough digraph 一种新的信任网络分析框架：基于连通性的直觉模糊粗有向图

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-09-05 DOI: 10.1016/j.ijar.2025.109564

Danyang Wang , Ping Zhu

{"title":"A novel framework for trust network analysis: Connectivity-based intuitionistic fuzzy rough digraph","authors":"Danyang Wang , Ping Zhu","doi":"10.1016/j.ijar.2025.109564","DOIUrl":"10.1016/j.ijar.2025.109564","url":null,"abstract":"<div><div>Network connectivity analysis enables information source tracing and spread regulation in social systems. While existing studies have explored intuitionistic fuzzy rough (IFR) digraphs to address the representation needs of pervasive uncertainties and dual-polarity information in real-world networks, their neglect of connectivity characteristics has limited applicability in information diffusion scenarios. This study breaks through conventional framework and proposes a connectivity-based IFR digraph model, which achieves comprehensive representation of information oppositionality, uncertainty, and propagative characteristic. First, we explore minimum equivalent intuitionistic fuzzy subgraph (MEIFS) and semi-maximum equivalent intuitionistic fuzzy supergraph (SEIFS). MEIFS preserves original strength of connectedness through minimal arc sets, while SEIFS achieves the same objective via redundant arc augmentation. This complementarity provides a mathematical tool for approximating complex networks. Then, a connectivity-based IFR digraph model is established through the synergy of MEIFS and SEIFS. Finally, according to the co-occurrence characteristics of trust and distrust in society, the community detection algorithm and multi-core-node mining method for IFR trust networks are developed. Comparative analysis with three existing methods demonstrates the superiority of the proposed technique in approximate modeling of adversarial information propagation systems.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109564"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing connectivity in fuzzy graphs for resilient disaster response networks 弹性灾害响应网络模糊图连通性优化

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-07-29 DOI: 10.1016/j.ijar.2025.109535

P Sujithra , Sunil Mathew , J.N. Mordeson

{"title":"Optimizing connectivity in fuzzy graphs for resilient disaster response networks","authors":"P Sujithra , Sunil Mathew , J.N. Mordeson","doi":"10.1016/j.ijar.2025.109535","DOIUrl":"10.1016/j.ijar.2025.109535","url":null,"abstract":"<div><div>Despite significant technological advances in recent years, communication challenges still persist. These issues are especially evident during crises, where system failures, network overloads, and incompatibilities among the communication technologies used by different organizations create major obstacles. Catastrophe scenarios are marked by high information uncertainty and limited control, which raises challenges for crisis communication. However, these aspects remain underexplored from a network-theoretic perspective. This study investigates the <span><math><mo>(</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>)</mo></math></span>-connectivity parameter between two nodes in a fuzzy graph, offering insights into network structure, robustness, and performance. We introduce a novel classification of nodes and edges into three categories: enhancing, eroded, and persisting, based on their impact on node-to-node connectivity. The behavior of these classifications is analyzed across different classes of fuzzy graphs. Furthermore, we establish upper and lower bounds for the <span><math><mo>(</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>)</mo></math></span>-connectivity under two graph operations. An efficient algorithm is proposed to identify and categorize nodes and edges accordingly. The practical relevance of our classification is illustrated through its application to disaster response communication networks, where maintaining resilient and adaptive communication is critical.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109535"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable multi-criteria decision-making: A three-way decision perspective 可解释的多准则决策：三向决策视角

IF 3.2 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-07-18 DOI: 10.1016/j.ijar.2025.109528

Chengjun Shi, Yiyu Yao

{"title":"Explainable multi-criteria decision-making: A three-way decision perspective","authors":"Chengjun Shi, Yiyu Yao","doi":"10.1016/j.ijar.2025.109528","DOIUrl":"10.1016/j.ijar.2025.109528","url":null,"abstract":"<div><div>This paper proposes an Explainable Multi-Criteria Decision-Making (XMCDM) framework that constructs trilevel explanations with respect to classic multi-criteria decision-making methods. The framework consists of explainable data preparation, explainable decision analysis, and explainable decision support, which integrates ideas from three-way decision and symbols-meaning-value spaces. First, we briefly introduce the key concepts at each level and list potential issues to be resolved, including gathering multi-criteria data, interpreting multi-criteria decision-making working principles, and offering effective outcome presentation. We examine existing literature that solves part of those questions and point out that rule-based explanations may be applicable and efficient to explain ranking/ordering results. Then, we discuss two methods that generate three-way rankings with respect to an individual criterion and integrate three-way rankings with multi-criteria ranking. We modify the Iterative Dichotomiser 3 algorithm to build rule-based explanations. Finally, after giving a small illustrative example, we design experiments on five real-life datasets, test explainability of three classic multi-criteria decision-making methods, and tune the thresholds. The experimental results demonstrate that our proposed framework is feasible and adaptable to various data characteristics.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109528"},"PeriodicalIF":3.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensitivity analysis to unobserved confounding with copula-based normalizing flows 基于copula的归一化流对未观测混杂的敏感性分析

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-07-30 DOI: 10.1016/j.ijar.2025.109531

Sourabh Balgi , Marc Braun , Jose M. Peña , Adel Daoud

{"title":"Sensitivity analysis to unobserved confounding with copula-based normalizing flows","authors":"Sourabh Balgi , Marc Braun , Jose M. Peña , Adel Daoud","doi":"10.1016/j.ijar.2025.109531","DOIUrl":"10.1016/j.ijar.2025.109531","url":null,"abstract":"<div><div>We propose a novel method for sensitivity analysis to unobserved confounding in causal inference. The method builds on a copula-based causal graphical normalizing flow that we term <em>ρ</em>-GNF, where <span><math><mi>ρ</mi><mo>∈</mo><mo>[</mo><mo>−</mo><mn>1</mn><mo>,</mo><mo>+</mo><mn>1</mn><mo>]</mo></math></span> is the sensitivity parameter. The parameter represents the non-causal association between exposure and outcome due to unobserved confounding, which is modeled as a Gaussian copula. In other words, the <em>ρ</em>-GNF enables scholars to estimate the average causal effect (ACE) as a function of <em>ρ</em>, accounting for various confounding strengths. The output of the <em>ρ</em>-GNF is what we term the <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi><mi>u</mi><mi>r</mi><mi>v</mi><mi>e</mi></mrow></msub></math></span>, which provides the bounds for the ACE given an interval of assumed <em>ρ</em> values. The <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi><mi>u</mi><mi>r</mi><mi>v</mi><mi>e</mi></mrow></msub></math></span> also enables scholars to identify the confounding strength required to nullify the ACE. We also propose a Bayesian version of our sensitivity analysis method. Assuming a prior over the sensitivity parameter <em>ρ</em> enables us to derive the posterior distribution over the ACE, which enables us to derive credible intervals. Finally, leveraging on experiments from simulated and real-world data, we show the benefits of our sensitivity analysis method.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109531"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The properties of 3-valued formal contexts in a cognitive viewpoint 认知视点下三值形式语境的性质

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-09-12 DOI: 10.1016/j.ijar.2025.109573

Huilai Zhi , Qing Wan , Ting Qian , Yinan Li , Jiang Yang

{"title":"The properties of 3-valued formal contexts in a cognitive viewpoint","authors":"Huilai Zhi , Qing Wan , Ting Qian , Yinan Li , Jiang Yang","doi":"10.1016/j.ijar.2025.109573","DOIUrl":"10.1016/j.ijar.2025.109573","url":null,"abstract":"<div><div>3-valued formal contexts are abstracted from various types of applications such as incomplete formal context based data mining, shadow sets based knowledge discovery and conflict analysis. 3-valued formal contexts differ from binary-valued formal contexts in many aspects, and many distinguished details have not been investigated. To this end, some of the most important properties of 3-valued formal contexts are systematically explored in a cognitive viewpoint based on formal concept analysis. At first, 3-valued concept lattices and formal concept lattices are compared from multiple perspectives, including the connections between formal concepts and 3-valued concepts, and the meet-preserving mappings from formal concept lattices to 3-valued concept lattices. After that, based on the completions of 3-valued contexts, the connections between 3-valued concept lattices and three-way concept lattices are explored. Finally, it is proved that a 3-valued concept lattice is the minimum closure that contains formal concept lattices, and there is an order-preserving mapping from formal concepts to equivalence classes of 3-valued concepts.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109573"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Some fuzzy neighborhood operators on fuzzy β-covering approximation space and their application in user preference evaluation 模糊β覆盖近似空间上的模糊邻域算子及其在用户偏好评价中的应用

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-09-08 DOI: 10.1016/j.ijar.2025.109566

Wei Li , Xiaolei Wang , Bin Yang

{"title":"Some fuzzy neighborhood operators on fuzzy β-covering approximation space and their application in user preference evaluation","authors":"Wei Li , Xiaolei Wang , Bin Yang","doi":"10.1016/j.ijar.2025.109566","DOIUrl":"10.1016/j.ijar.2025.109566","url":null,"abstract":"<div><div>As a generalization of covering, fuzzy <em>β</em>-covering provides a more accurate and practical representation for incomplete information. This paper primarily proposes several fuzzy neighborhood operators based on diverse aggregation functions in an fuzzy <em>β</em>-covering approximation space (F<em>β</em>CAS) and develops a novel TOPSIS method to address the decision-making problem related to user preference factors. First, two classes of fuzzy neighborhood operators are introduced, derived from <em>t</em>-norms, overlap functions and their residual implications in an F<em>β</em>CAS, with their properties thoroughly analyzed. In addition, multiple fuzzy <em>β</em>-coverings are generated from the original fuzzy <em>β</em>-covering, and the classifications of fuzzy neighborhood operators, along with their partial order relationships, are examined. Based on these operators, two kinds of fuzzy <em>β</em>-covering-based rough sets (F<em>β</em>CRS) are established. Finally, an F<em>β</em>CRS-based fuzzy TOPSIS method is developed to evaluate user preference factors for fresh fruit, thereby demonstrating the rationality and feasibility of the proposed approach.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109566"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145044513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fusing fuzzy rough sets and mean shift for anomaly detection 基于模糊粗糙集和均值移位的异常检测

IF 3 3区计算机科学

International Journal of Approximate Reasoning Pub Date : 2025-12-01 Epub Date: 2025-07-18 DOI: 10.1016/j.ijar.2025.109530

Mengyao Liao , Zhiyu Chen , Can Gao , Jie Zhou , Xiaodong Yue

{"title":"Fusing fuzzy rough sets and mean shift for anomaly detection","authors":"Mengyao Liao , Zhiyu Chen , Can Gao , Jie Zhou , Xiaodong Yue","doi":"10.1016/j.ijar.2025.109530","DOIUrl":"10.1016/j.ijar.2025.109530","url":null,"abstract":"<div><div>Outlier detection is a critical but challenging task due to the complex distribution of practical data, and some Fuzzy Rough Sets (FRS)-based methods have been presented to identify outliers from these data. However, these methods still have limitations when facing the co-existence of different types of outliers. In this study, an improved FRS-based unsupervised anomaly detection method is proposed by integrating distance and density information. Specifically, to detect the local outliers, a fuzzy granule density is first defined by introducing a Gaussian kernel similarity to characterize the local density of samples. Then, optimistic and pessimistic fuzzy granule densities are further developed to evaluate the density variation in the local neighborhood. Moreover, a distance measure based on mean shift is introduced to detect global and group outliers. Finally, an outlier detection method that integrates the density and distance measures is designed to effectively identify diverse types of outliers. Extensive experiments on synthetic and public datasets, along with statistical significance analysis, demonstrate the superior performance of the proposed method, achieving an average improvement of at least 12.27% in terms of AUROC.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"187 ","pages":"Article 109530"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0