Fuzzy Sets and Systems最新文献

Soft-neighborhood based robust fuzzy rough sets for semi-supervised feature selection

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-04-01 DOI: 10.1016/j.fss.2025.109397

Shuang An , Yuhang Gong , Changzhong Wang , Ge Guo

{"title":"Soft-neighborhood based robust fuzzy rough sets for semi-supervised feature selection","authors":"Shuang An , Yuhang Gong , Changzhong Wang , Ge Guo","doi":"10.1016/j.fss.2025.109397","DOIUrl":"10.1016/j.fss.2025.109397","url":null,"abstract":"<div><div>Fuzzy rough set (FRS) theory has been widely concerned because of its successful application in dimensionality reduction of data. To reduce the sensitivity of the theory to noise and data distribution in practical applications, the study of robust FRS model still attracts great attention. This research is devoted to the robust fuzzy rough uncertainty measure theory for multi-density data. Firstly, soft-neighborhood theory is combined with classical FRSs to design a generalized FRS model which is simply named SNFRS. The new model can effectively reduce the influence of noise and multi-density distribution on uncertainty measure of data. Secondly, with the SNFRS model, soft fuzzy rough indiscernibility theory is proposed, and it is used to design feature selection algorithms. In this research, a fully supervised feature selection and a semi-supervised feature selection algorithms are respectively proposed based on the soft fuzzy rough indiscernibility theory. Besides, the labeling method of the semi-supervised feature selection is also based on the theory. Finally, some experiments are performed to verify the proposed models and algorithms. The results show that the feature selection algorithms based on the soft fuzzy rough indiscernibility are feasible and efficient. This indirectly indicates that the FRS model based on soft-neighborhood is effective, successful and generalized in measuring uncertainty of data.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109397"},"PeriodicalIF":3.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759326","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}

引用次数: 0

Synthetic static output feedback control for fuzzy systems under fault derivative transformation based fault accommodation

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-28 DOI: 10.1016/j.fss.2025.109396

Hong-Jun Wang , Sheng-Juan Huang

引用次数: 0

Novel stability analysis and intelligent control of uncertain impulsive stochastic nonlinear systems with applications

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-28 DOI: 10.1016/j.fss.2025.109386

Changan Shao, Huasheng Zhang

{"title":"Novel stability analysis and intelligent control of uncertain impulsive stochastic nonlinear systems with applications","authors":"Changan Shao, Huasheng Zhang","doi":"10.1016/j.fss.2025.109386","DOIUrl":"10.1016/j.fss.2025.109386","url":null,"abstract":"<div><div>A new operator is proposed for uncertain impulsive stochastic nonlinear systems (UISNSs) based on the T-S fuzzy model and the pole configuration principle. The definition of interval stability of the system is given using this operator. The application of interval stability theory to parameter uncertain systems is extended. Different from the general concept of stability, interval stability can not only determine the stability of the system but also reflect the convergence rate (CR) of the system. The fuzzy state feedback controllers with adjustable CR are further designed. Compared with most existing fuzzy controllers, our designed controllers can control the system more accurately, i.e., effectively constrain the CR of the system. Moreover, a new design method for an <span><math><msub><mrow><mi>H</mi></mrow><mrow><mo>∞</mo></mrow></msub></math></span> fuzzy controller based on interval stability is proposed, which can constrain the CR of the system while satisfying certain performance. Finally, the feasibility and applicability of these methods are verified by Chua's circuit model, the cart inverted pendulum model, and numerical experiments.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"513 ","pages":"Article 109386"},"PeriodicalIF":3.2,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739657","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}

引用次数: 0

An improved fault and state interval estimator for uncertain Takagi-Sugeno fuzzy systems

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-27 DOI: 10.1016/j.fss.2025.109383

Lanshuang Zhang , Zhenhua Wang , Choon Ki Ahn , Juntao Pan , Yi Shen

{"title":"An improved fault and state interval estimator for uncertain Takagi-Sugeno fuzzy systems","authors":"Lanshuang Zhang , Zhenhua Wang , Choon Ki Ahn , Juntao Pan , 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}

引用次数: 0

Aggregation functions as lax morphisms of quantales

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-27 DOI: 10.1016/j.fss.2025.109395

Alejandro Fructuoso-Bonet, Jesús Rodríguez-López

引用次数: 0

Idempotent pseudo-n-uninorms

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-26 DOI: 10.1016/j.fss.2025.109387

Juraj Kalafut , Andrea Mesiarová-Zemánková

引用次数: 0

Extending intuitionistic operations, orderings, and entropy measures on generalized fuzzy orthopartitions

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-26 DOI: 10.1016/j.fss.2025.109381

Stefania Boffa , Davide Ciucci , Christophe Marsala

引用次数: 0

Discernibility matrix-based feature selection approaches with fuzzy dominance-based neighborhood rough sets

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-25 DOI: 10.1016/j.fss.2025.109384

Jiayue Chen , Ping Zhu

{"title":"Discernibility matrix-based feature selection approaches with fuzzy dominance-based neighborhood rough sets","authors":"Jiayue Chen , 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}

引用次数: 0

A novel method for incremental feature selection with fuzzy β-covering

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-24 DOI: 10.1016/j.fss.2025.109379

Tianyu Wang, Shuai Liu, Bin Yang

{"title":"A novel method for incremental feature selection with fuzzy β-covering","authors":"Tianyu Wang, Shuai Liu, 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}

引用次数: 0

A short note about a practical procedure for the calculus of the Sugeno integral

IF 3.2 1区数学

Fuzzy Sets and Systems Pub Date : 2025-03-24 DOI: 10.1016/j.fss.2025.109385

J. Caballero, B. López, K. Sadarangani

引用次数: 0