Fuzzy Sets and Systems最新文献

{"title":"An improved fault and state interval estimator for uncertain Takagi-Sugeno fuzzy systems","authors":"Lanshuang Zhang ,&nbsp;Zhenhua Wang ,&nbsp;Choon Ki Ahn ,&nbsp;Juntao Pan ,&nbsp;Yi Shen","doi":"10.1016/j.fss.2025.109383","DOIUrl":"10.1016/j.fss.2025.109383","url":null,"abstract":"<div><div>This paper investigates the simultaneous interval estimation of the fault and state for uncertain Takagi-Sugeno fuzzy systems under the fault. An improved fault and state interval estimator is presented to better estimate the values of fault and state with corresponding tight adaptive intervals. By using the state argument method, the considered system is reformulated in the form of an argument system. Then, based on the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> optimization method, a novel fault and state interval estimator that can simultaneously and independently minimize the widths of the intervals enclosing each state component is proposed, which has clear geometric meaning and more design freedom degrees. The zonotopic Kalman filter and the observer with <em>K</em>-<em>L</em> structure can be regarded as special forms of the proposed estimator. Finally, we apply the presented approach to a lateral vehicle system to verify the superiority. Compared with the Frobenius norm optimization method and an advanced interval estimation method, the presented approach can improve the performance of the interval estimation and obtain more tight adaptive intervals.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109383"},"PeriodicalIF":3.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aggregation functions as lax morphisms of quantales","authors":"Alejandro Fructuoso-Bonet,&nbsp;Jesús Rodríguez-López","doi":"10.1016/j.fss.2025.109395","DOIUrl":"10.1016/j.fss.2025.109395","url":null,"abstract":"<div><div>We will generalize the concept of aggregation function for mathematical structures as a certain function between quantales. In fact, these functions turn to be exactly the lax morphism of quantales. This provides a global framework for the study of aggregation functions. As a consequence of our theory, we are able to deduce several known results about the aggregation of metrics and fuzzy metrics.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109395"},"PeriodicalIF":3.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Idempotent pseudo-n-uninorms","authors":"Juraj Kalafut ,&nbsp;Andrea Mesiarová-Zemánková","doi":"10.1016/j.fss.2025.109387","DOIUrl":"10.1016/j.fss.2025.109387","url":null,"abstract":"<div><div>The structure of idempotent pseudo-<em>n</em>-uninorms, non-commutative generalizations of idempotent <em>n</em>-uninorms, is investigated. First, idempotent pseudo-2-uninorms are characterized by their decomposition into an idempotent pseudo-uninorm and a special idempotent pseudo-2-uninorm, for which the division point <em>z</em> is a (left/right) annihilator. These results are then used in characterization of all idempotent pseudo-<em>n</em>-uninorms by decomposition based on their set of left (right) annihilators and Clifford's ordinal sum. The achieved results reveal that the structure of pseudo-<em>n</em>-uninorms is significantly different from that of <em>n</em>-uninorms and general pseudo-<em>n</em>-uninorms cannot be decomposed via <em>z</em>-ordinal sum. These results provide new insights into the nature of non-commutative aggregation functions.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109387"},"PeriodicalIF":3.2,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extending intuitionistic operations, orderings, and entropy measures on generalized fuzzy orthopartitions","authors":"Stefania Boffa ,&nbsp;Davide Ciucci ,&nbsp;Christophe Marsala","doi":"10.1016/j.fss.2025.109381","DOIUrl":"10.1016/j.fss.2025.109381","url":null,"abstract":"<div><div>Generalized fuzzy orthopartitions extend the traditional concept of partitions to include both fuzziness and uncertainty. A generalized fuzzy orthopartition is a collection of intuitionistic fuzzy sets representing equivalence classes and satisfying a specific pair of axioms, which capture the idea that the classes must be disjoint and cover the initial universe. The aim of this article is twofold. Firstly, we aggregate and order generalized fuzzy orthopartitions by extending intuitionistic operations and relations. Secondly, we introduce and study entropy measures on generalized fuzzy orthopartitions by employing entropies on intuitionistic fuzzy sets already existing in the literature.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109381"},"PeriodicalIF":3.2,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discernibility matrix-based feature selection approaches with fuzzy dominance-based neighborhood rough sets","authors":"Jiayue Chen ,&nbsp;Ping Zhu","doi":"10.1016/j.fss.2025.109384","DOIUrl":"10.1016/j.fss.2025.109384","url":null,"abstract":"<div><div>Monotonic classification tasks (MCTs) are a critical type of classification tasks, characterized by the monotonic constraints between features and decision. As an essential dimensionality reduction technique, feature selection using discernibility matrices (DMs) has gained considerable attention. Relevant studies in MCTs have effectively addressed the construction of DMs, followed by the reduct computation via the discernibility function method. However, they remain restricted within crisp dominance rough sets (DRSs) and overlook other potential usages of DMs in feature selection. To address these issues, this paper constructs a DM based on a fuzzy DRS model and combines it with feature grouping to propose a composite feature selection algorithm for MCTs, termed DMCD. Firstly, fuzzy dominance-based neighborhood rough sets are established as the theoretical foundation, and a DM corresponding to fuzzy rank dependency is constructed. The discernibility function method can thus be employed to calculate all the reducts. Next, we use the DM to quantify the discriminative power of features and design a fuzzy-rank-entropy-based distance measure, which is then employed to group features with similar classification information. At each iteration of DMCD, the most discriminative features carrying distinct classification information are selected from these groups and sequenced. After this procedure, a wrapper technique is applied to derive the optimal feature subset. Finally, experiments on twenty real datasets demonstrate the robustness of the FDNRS model and the effectiveness of the DMCD algorithm.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109384"},"PeriodicalIF":3.2,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel method for incremental feature selection with fuzzy β-covering","authors":"Tianyu Wang,&nbsp;Shuai Liu,&nbsp;Bin Yang","doi":"10.1016/j.fss.2025.109379","DOIUrl":"10.1016/j.fss.2025.109379","url":null,"abstract":"<div><div>Fuzzy <em>β</em>-covering has attracted significant academic attention due to its enhanced capability in representing uncertain information, surpassing traditional fuzzy covering approaches. However, the initial formulation of fuzzy <em>β</em>-covering rough sets fails to guarantee the inclusion relation between the upper and lower approximations. In addition, unlike partitions, coverings may contain redundant elements while still satisfying the covering property, making it crucial to assess whether any redundant elements are present. Nevertheless, the incremental mechanism for the reduct of fuzzy <em>β</em>-covering is still unclear. To address these limitations, we first introduce generalized fuzzy <em>β</em>-neighborhoods and derive the corresponding fuzzy <em>β</em>-covering rough sets, ensuring the inclusion relation between the upper and lower approximations. On this basis, a feature selection method with fuzzy <em>β</em>-covering based on relative discernibility relation is proposed, which only calculates the fuzzy positive region in the process of obtaining relative discernibility relation. Furthermore, to investigate incremental mechanisms for reduct of fuzzy <em>β</em>-covering, we develop novel incremental feature selection algorithms for fuzzy <em>β</em>-covering. Experimental comparisons with both non-incremental and incremental algorithms demonstrate that our proposed methods effectively identify the reduct of fuzzy <em>β</em>-covering, showcasing superior computational efficiency.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"512 ","pages":"Article 109379"},"PeriodicalIF":3.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A short note about a practical procedure for the calculus of the Sugeno integral","authors":"J. Caballero,&nbsp;B. López,&nbsp;K. Sadarangani","doi":"10.1016/j.fss.2025.109385","DOIUrl":"10.1016/j.fss.2025.109385","url":null,"abstract":"<div><div>In this note, we present a practical method for the computation of the Sugeno integral of a nonnegative measurable function with respect to a general monotone measure.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"512 ","pages":"Article 109385"},"PeriodicalIF":3.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radon-Nikodým theorems for generalized fuzzy number measures","authors":"Sokol Bush Kaliaj","doi":"10.1016/j.fss.2025.109380","DOIUrl":"10.1016/j.fss.2025.109380","url":null,"abstract":"&lt;div&gt;&lt;div&gt;In this paper we deal with generalized fuzzy number measures defined on Σ and taking values in the set &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt;, where &lt;span&gt;&lt;math&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;Ω&lt;/mi&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mi&gt;Σ&lt;/mi&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mi&gt;μ&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; is a complete finite measure space, &lt;span&gt;&lt;math&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; is the family of all non-empty convex weakly compact subsets of a Banach space &lt;em&gt;X&lt;/em&gt; and &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; is such that a fuzzy set &lt;span&gt;&lt;math&gt;&lt;mi&gt;u&lt;/mi&gt;&lt;mo&gt;:&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;→&lt;/mo&gt;&lt;mo&gt;[&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; is a member of &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; if and only if&lt;span&gt;&lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mo&gt;[&lt;/mo&gt;&lt;mi&gt;u&lt;/mi&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mtext&gt; for all &lt;/mtext&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mo&gt;[&lt;/mo&gt;&lt;mi&gt;u&lt;/mi&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mo&gt;{&lt;/mo&gt;&lt;mi&gt;x&lt;/mi&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;:&lt;/mo&gt;&lt;mi&gt;u&lt;/mi&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;x&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;mo&gt;}&lt;/mo&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt; We show two Radon-Nikodým theorems for such generalized fuzzy number measures in terms of Pettis integral of fuzzy mappings. The first theorem works for a &lt;em&gt;μ&lt;/em&gt;-continuous generalized fuzzy number measure &lt;span&gt;&lt;math&gt;&lt;mi&gt;M&lt;/mi&gt;&lt;mo&gt;:&lt;/mo&gt;&lt;mi&gt;Σ&lt;/mi&gt;&lt;mo&gt;→&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; of bounded variation in a Banach space &lt;em&gt;X&lt;/em&gt; with the Radon-Nikodým property (RNP). The next theorem shows that if a generalized fuzzy number measure &lt;span&gt;&lt;math&gt;&lt;mi&gt;M&lt;/mi&gt;&lt;mo&gt;:&lt;/mo&gt;&lt;mi&gt;Σ&lt;/mi&gt;&lt;mo&gt;→&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; is “dominated” by a generalized fuzzy number &lt;span&gt;&lt;math&gt;&lt;mi&gt;Q&lt;/mi&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;c&lt;/mi&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/math&gt;&lt;/span&gt; in terms of &lt;em&gt;α&lt;/em&gt;-level sets, i.e.,&lt;span&gt;&lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mo&gt;[&lt;/mo&gt;&lt;mi&gt;M&lt;/mi&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mo&gt;⊂&lt;/mo&gt;&lt;mi&gt;μ&lt;/mi&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mo&gt;[&lt;/mo&gt;&lt;mi&gt;Q&lt;/mi&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mtext&gt; for all &lt;/mtext&gt;&lt;mi&gt;A&lt;/mi&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;mi&gt;Σ&lt;/mi&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mi&gt;α&lt;/mi&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/sp","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"512 ","pages":"Article 109380"},"PeriodicalIF":3.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Asynchronous membership functions decoupling based event-triggered fuzzy networked control for nonlinear systems","authors":"Wen-Bo Xie ,&nbsp;Yong-Qi Wu ,&nbsp;Shi-Qi Zheng ,&nbsp;Yu-Long Wang","doi":"10.1016/j.fss.2025.109377","DOIUrl":"10.1016/j.fss.2025.109377","url":null,"abstract":"<div><div>This paper focuses on the <span><math><msub><mrow><mi>H</mi></mrow><mrow><mo>∞</mo></mrow></msub></math></span> robust control for a kind of nonlinear networked control systems depicted by T-S fuzzy form model. An event-triggered communication scheme is adopted to improve the utilization of network resources. A new fuzzy system model is derived by designing an asynchronous membership functions decoupling method, such that more information about the membership functions is involved in the process of stability and robustness analysis. Based on Lyapunov Krasovskii Functional (LKF) method, a series of convex stability and robustness conditions can be given. Finally, two benchmark examples are introduced to prove the effectiveness of the designed method.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"512 ","pages":"Article 109377"},"PeriodicalIF":3.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fuzzy neighborhood based variable-precision granular-ball rough sets with applications to feature selection","authors":"Yongxi Chen ,&nbsp;Zhehuang Huang ,&nbsp;Jinjin Li","doi":"10.1016/j.fss.2025.109382","DOIUrl":"10.1016/j.fss.2025.109382","url":null,"abstract":"<div><div>Granular-ball computing is an efficient, simple and scalable computing paradigm that has emerged in recent years. By sampling the data with multiple divisions, the knowledge on different granularity levels is obtained, so as to achieve the purpose of multi-granularity data analysis. As a representative model of granular-ball computing, granular ball neighborhood rough set model (GBNRS) offers greater generality and flexibility as it can adaptively generate different neighborhood radii for each object. However, GBNRS consistently sets the purity degree with 1 for all granular-balls, which may lead to poor fault tolerance in uncertain information systems. Additionally, GBNRS lacks effective approximation operators, making it hard to effectively characterize the differences among samples. For these reasons, a new variable-precision rough set model is set forth by combining granular-ball rough sets, fuzzy rough sets and neighborhood rough sets. To this end, a granular-ball fuzzy neighborhood is presented to reflect the similarity of the samples and a pair of variable-precision approximation operators is formulated to improve the noise-tolerant ability. On this basis, a new granular-ball rough set model i.e. fuzzy neighborhood based granular-ball rough sets (FNGBRS) is proposed. Furthermore, a variable-precision dependency function is introduced to evaluate the classification ability of a given feature sets at different granularity levels. The dimensionality reduction of decision systems is carried out under the condition of keeping the classification ability unchanged, and a feature selection algorithm is developed by using the variable-precision dependency function. Numerical experiments on 12 different types of datasets demonstrate that the proposed model outperforms some state-of-the-art feature learning algorithms in terms of classification accuracy and the number of selected features.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"512 ","pages":"Article 109382"},"PeriodicalIF":3.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}