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International Journal of Approximate Reasoning最新文献

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Further studies on abstract rough inclusion properties
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2025-01-02 DOI: 10.1016/j.ijar.2024.109356
Anirban Saha , Jayanta Sen , Mihir Kumar Chakraborty
{"title":"Further studies on abstract rough inclusion properties","authors":"Anirban Saha ,&nbsp;Jayanta Sen ,&nbsp;Mihir Kumar Chakraborty","doi":"10.1016/j.ijar.2024.109356","DOIUrl":"10.1016/j.ijar.2024.109356","url":null,"abstract":"<div><div>The rough set theoretic motivation for abstract rough inclusion properties is presented here. Several algebraic structures between <strong>System algebras</strong> and <strong>pre-rough algebra</strong> have been defined. These algebras depend on the addition of abstract rough inclusion properties to the <strong>System algebras</strong>. Weak residuations with respect to rough implication are investigated in these algebras. Sequent calculi and Hilbert systems for these algebraic structures are obtained. Logical interpretation of weak residuation property is provided.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109356"},"PeriodicalIF":3.2,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141389","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
Attribute reduction method based on fuzzy relational equations and inequalities
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-27 DOI: 10.1016/j.ijar.2024.109355
Zofia Matusiewicz, Teresa Mroczek
{"title":"Attribute reduction method based on fuzzy relational equations and inequalities","authors":"Zofia Matusiewicz,&nbsp;Teresa Mroczek","doi":"10.1016/j.ijar.2024.109355","DOIUrl":"10.1016/j.ijar.2024.109355","url":null,"abstract":"<div><div>Attribute selection is essential in machine learning for simplifying problems, reducing dimensionality, and enhancing computational efficiency. This article introduces a novel approach with linear time complexity for identifying the strongest dependencies between attributes and decisions, utilizing fuzzy relational equations and inequalities. The approach includes a concept that employs a binarized, reduced matrix to establish the reduction threshold. The effectiveness of this new attribute reduction method was evaluated using five different types of relational compositions with continuous triangular norms. Experimental results demonstrate that the proposed method achieves comparable accuracy to well-known reduction algorithms, while offering greater computational efficiency.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109355"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141388","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
Integral algebra for simulating dynamical systems with interval uncertainties
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-27 DOI: 10.1016/j.ijar.2024.109353
Luc Jaulin
{"title":"Integral algebra for simulating dynamical systems with interval uncertainties","authors":"Luc Jaulin","doi":"10.1016/j.ijar.2024.109353","DOIUrl":"10.1016/j.ijar.2024.109353","url":null,"abstract":"<div><div>This paper presents an integral algebra and shows how it can be used to simulate a dynamical system with interval uncertainties. These uncertainties, can be either on the initial state vector, on the time-dependent inputs, or on the evolution function. Compared to other techniques used for the guaranteed integration of differential inclusion, the presented approach does not require the use of a fixed-point Picard operator. Two test-cases related to robotics are presented to illustrate the efficiency of the approach.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109353"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141985","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
Attribute reduction based on weighted neighborhood constrained fuzzy rough sets induced by grouping functions
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-25 DOI: 10.1016/j.ijar.2024.109354
Shan He , Junsheng Qiao , Chengxi Jian
{"title":"Attribute reduction based on weighted neighborhood constrained fuzzy rough sets induced by grouping functions","authors":"Shan He ,&nbsp;Junsheng Qiao ,&nbsp;Chengxi Jian","doi":"10.1016/j.ijar.2024.109354","DOIUrl":"10.1016/j.ijar.2024.109354","url":null,"abstract":"<div><div>Attribute reduction can extract the most critical attributes from multi-dimensional datasets, this reduces data dimensionality, simplifies data processing and analysis, and the fuzzy rough set (FRS) model-based attribute reduction method is one of the most commonly used attribute reduction methods. In this paper, we construct a new FRS model named G-WNC-FRS for attribute reduction by introducing a new inter-sample distance and two aggregation functions. Specifically, we first introduce the weighted neighborhood constrained distance between samples to make the difference in attributes between different class samples obvious. Then we introduce two not necessarily associative aggregation functions, overlap and grouping functions, to replace the commonly used triangular norms and triangular conorms in FRS model. Finally, we design G-WNC-FRS-based attribute reduction algorithm to select important attributes for classification tasks. Numerical experiments on 11 datasets demonstrate that the attribute reduction algorithm based on G-WNC-FRS has a strong ability to eliminate redundant attributes. Additionally, noise experiments and sensitivity experiments on 4 datasets show that the algorithm has high noise immunity and is able to adapt to different types of datasets.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109354"},"PeriodicalIF":3.2,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141991","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
Measures of association and dependence properties of nested random sets
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-19 DOI: 10.1016/j.ijar.2024.109352
Bernhard Schmelzer
{"title":"Measures of association and dependence properties of nested random sets","authors":"Bernhard Schmelzer","doi":"10.1016/j.ijar.2024.109352","DOIUrl":"10.1016/j.ijar.2024.109352","url":null,"abstract":"<div><div>The aim of this paper is to demonstrate how measures of association and dependence properties that are well-known for random variables can be defined for nested random sets. More precisely, definitions of Kendall's tau, Spearman's rho, quadrant dependence, tail monotonicity, stochastic monotonicity and tail dependence are provided. In a previous paper, the author presented a version of Sklar's theorem for nested random sets, i.e., it was shown that the joint distribution of nested random sets is linked to its marginals via a copula. Using this result it is shown that the aforementioned measures of association and dependence properties are properties of the copula if the nested random sets are nonatomic – similarly, as it is the case for continuous random variables. A characterization of nonatomicity based on the (one-point) covering function is provided and a probability integral transform for nonatomic nested random closed sets is proven.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109352"},"PeriodicalIF":3.2,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141393","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
Integration of evolutionary prejudices in Dempster-Shafer theory
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-12 DOI: 10.1016/j.ijar.2024.109351
Florence Dupin de Saint-Cyr, Francis Faux
{"title":"Integration of evolutionary prejudices in Dempster-Shafer theory","authors":"Florence Dupin de Saint-Cyr,&nbsp;Francis Faux","doi":"10.1016/j.ijar.2024.109351","DOIUrl":"10.1016/j.ijar.2024.109351","url":null,"abstract":"<div><div>This paper deals with belief change in the framework of Dempster-Shafer theory in the context where an agent has a prejudice, i.e., a priori knowledge about a situation. Our study is based on a review of the literature in the social sciences and humanities. Our framework relies on the claim that prejudices and evidences should be dealt with separately because of their very different natures (prejudices being at the meta level, governing the evolution of beliefs). Hence, the cognitive state of an agent is modeled as a pair whose components reflect its prejudices and uncertain beliefs. We propose a general formalism for encoding the evolution of this pair when new information arrives, this is why the study is related to Dempster's revision. Several cases of prejudice are described: the strong persistent prejudice (which never evolves and forbids beliefs to change), the prejudice that is slightly decreasing each time a belief contradicts it, etc. A general example with several prejudices and complex masses illustrates our approach.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109351"},"PeriodicalIF":3.2,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141988","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
Generalized multiview sequential three-way decisions based on local partition order product space
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-09 DOI: 10.1016/j.ijar.2024.109350
Jin Qian , Chuanpeng Zhou , Ying Yu , Mingchen Zheng , Chengxin Hong , Hui Wang
{"title":"Generalized multiview sequential three-way decisions based on local partition order product space","authors":"Jin Qian ,&nbsp;Chuanpeng Zhou ,&nbsp;Ying Yu ,&nbsp;Mingchen Zheng ,&nbsp;Chengxin Hong ,&nbsp;Hui Wang","doi":"10.1016/j.ijar.2024.109350","DOIUrl":"10.1016/j.ijar.2024.109350","url":null,"abstract":"<div><div>The hierarchical sequential three-way decision model is a method for addressing complex problem-solving. The existing hierarchical sequential three-way decision models mostly employ multi-view and/or multi-level approaches. However, as the number of views increases and the levels deepen, the model becomes too large to solve problems efficiently. In order to solve this problem, this paper proposes a generalized multiview hierarchical sequential three-way decisions based on local partition order product space model. Specifically, we first use a nested partition sequence to represent a view. Next, the linear order relations between levels within the views are split according to the number of levels to obtain local linear order relations. Then, in the multiple views, the local linear order relations between levels close to each other from different views are combined using Cartesian product operations to construct a generalized local partition order product space. Finally, by integrating the hierarchical sequential three-way decisions, the generalized local partition order product space is transformed into a multiview hierarchical sequential three-way decisions model. Experimental results on multiple datasets demonstrate that the proposed multiview hierarchical sequential three-way decision model achieves better performance compared to the existing models.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109350"},"PeriodicalIF":3.2,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141989","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
Multi-label learning based on neighborhood rough set label-specific features
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-06 DOI: 10.1016/j.ijar.2024.109349
Jiadong Zhang, Jingjing Song, Huige Li, Xun Wang, Xibei Yang
{"title":"Multi-label learning based on neighborhood rough set label-specific features","authors":"Jiadong Zhang,&nbsp;Jingjing Song,&nbsp;Huige Li,&nbsp;Xun Wang,&nbsp;Xibei Yang","doi":"10.1016/j.ijar.2024.109349","DOIUrl":"10.1016/j.ijar.2024.109349","url":null,"abstract":"<div><div>Multi-label learning emerges as a novel paradigm harnessing diverse semantic datasets. Its objective involves eliciting a prognostic framework capable of allocating correlated labels to an unseen instance. Within the multifaceted domain of multi-label learning, the adoption of a label-specific feature methodology is prevalent. This approach entails the induction of a classification model that forecasts the relevance of each class label, utilizing tailored features specific to each label rather than relying on the original features. However, some irrelevant or redundant features will inevitably be generated when constructing features. To address this issue, we extend the current approach and introduce a straightforward yet potent multi-label learning method named NRS-LIFT, i.e., Neighborhood Rough Set Label-specIfic FeaTures. Specifically, a sample selection method is used to reduce the computational complexity, and then a set of tailored features is customized for each label through the neighborhood rough set. Finally, a learning model is induced to predict unseen instances. To fully evaluate the effectiveness of NRS-LIFT, we conduct extensive experiments on 12 multi-label datasets. Compared with mature multi-label learning methods, it is verified that NRS-LIFT has strong performance for multi-label datasets.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109349"},"PeriodicalIF":3.2,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141990","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
Simple contrapositive assumption-based argumentation frameworks with preferences: Partial orders and collective attacks
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-03 DOI: 10.1016/j.ijar.2024.109340
Ofer Arieli , Jesse Heyninck
{"title":"Simple contrapositive assumption-based argumentation frameworks with preferences: Partial orders and collective attacks","authors":"Ofer Arieli ,&nbsp;Jesse Heyninck","doi":"10.1016/j.ijar.2024.109340","DOIUrl":"10.1016/j.ijar.2024.109340","url":null,"abstract":"<div><div>In this paper, we consider assumption-based argumentation frameworks that are based on contrapositive logics and partially-ordered preference functions. It is shown that these structures provide a general and solid platform for representing and reasoning with conflicting and prioritized arguments. Two useful properties of the preference functions are identified (selectivity and max-lower-boundedness), and extended forms of attack relations are supported (∃–attacks and ∀-attacks), which assure several desirable properties and a variety of formal settings for argumentation-based conclusion drawing. These two variations of attacks may be further extended to collective attacks. Such (existential or universal) collective attacks allow to challenge a collective of assertions rather than single assertions. We show that these extensions not only enhance the expressive power of the framework, but in certain cases also enable more rational patterns of reasoning with conflicting assertions.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109340"},"PeriodicalIF":3.2,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141986","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
Interactive preference elicitation under noisy preference models: An efficient non-Bayesian approach
IF 3.2 3区 计算机科学
International Journal of Approximate Reasoning Pub Date : 2024-12-02 DOI: 10.1016/j.ijar.2024.109333
Guillaume Escamocher , Samira Pourkhajouei , Federico Toffano , Paolo Viappiani , Nic Wilson
{"title":"Interactive preference elicitation under noisy preference models: An efficient non-Bayesian approach","authors":"Guillaume Escamocher ,&nbsp;Samira Pourkhajouei ,&nbsp;Federico Toffano ,&nbsp;Paolo Viappiani ,&nbsp;Nic Wilson","doi":"10.1016/j.ijar.2024.109333","DOIUrl":"10.1016/j.ijar.2024.109333","url":null,"abstract":"<div><div>The development of models that can cope with noisy input preferences is a critical topic in artificial intelligence methods for interactive preference elicitation. A Bayesian representation of the uncertainty in the user preference model can be used to successfully handle this, but there are large costs in terms of the processing time which limit the adoption of these techniques in real-time contexts. A Bayesian approach also requires one to assume a prior distribution over the set of user preference models. In this work, dealing with multi-criteria decision problems, we consider instead a more qualitative approach to preference uncertainty, focusing on the most plausible user preference models, and aim to generate a query strategy that enables us to find an alternative that is optimal in all of the most plausible preference models. We develop a non-Bayesian algorithmic method for recommendation and interactive elicitation that considers a large number of possible user models that are evaluated with respect to their degree of consistency of the input preferences. This suggests methods for generating queries that are reasonably fast to compute. We show formal asymptotic results for our algorithm, including the probability that it returns the actual best option. Our test results demonstrate the viability of our approach, including in real-time contexts, with high accuracy in recommending the most preferred alternative for the user.</div></div>","PeriodicalId":13842,"journal":{"name":"International Journal of Approximate Reasoning","volume":"178 ","pages":"Article 109333"},"PeriodicalIF":3.2,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143141987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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