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Simultaneous fault detection and robust control for a dynamic observer-based switched time delay systems with car roll dynamic application 基于动态观测器的汽车滚动动态切换时滞系统故障检测与鲁棒控制
4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-09-21 DOI: 10.1080/03081079.2023.2248359
M. R. Shokrollahi, A. K. Mousavi
AbstractIn this study, the issue of simultaneous fault detection and control (SFDC) for a class of switched linear systems with input and state delays is being addressed. A detector/controller unit (dynamic observer/observer-based controller) is suggested for a residual generation that simultaneously takes into account the control and fault detection objectives using specific performance indices. It is assumed that the delay will fluctuate within a range with a lower bound that is not zero. Based on a Lyapunov–Krasovskii functional (LKF), and thanks to the free-weighting matrix and projection lemma, a new sufficient condition for developing a new method is put forth in terms of a set of linear matrix inequalities (LMIs). To illustrate how well the suggested results work, the proposed method is applied to a vehicle roll dynamic.KEYWORDS: Fault detection and controltime delay systemsdynamic observerlinear matrix inequalitycar roll dynamic Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementData sharing not applicable to this article as no datasets were generated or analyzed during the current study.
摘要本文研究了一类具有输入和状态延迟的切换线性系统的同步故障检测与控制问题。对于残差生成,建议使用检测器/控制器单元(动态观测器/基于观测器的控制器)同时考虑使用特定性能指标的控制和故障检测目标。假设延迟将在一个下界不为零的范围内波动。在Lyapunov-Krasovskii泛函(LKF)的基础上,利用自由加权矩阵和投影引理,给出了一组线性矩阵不等式(lmi)发展新方法的充分条件。为了说明所建议的结果是如何工作的,所提出的方法是应用于车辆侧倾动态。关键词:故障检测与控制时滞系统动态观测器线性矩阵不等式小车滚动动态披露声明作者未报告潜在利益冲突。数据可用性声明数据共享不适用于本文,因为在当前研究期间没有生成或分析数据集。
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引用次数: 0
Skill hierarchy structure based skill assessment and learning paths 基于技能评估和学习路径的技能层次结构
4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-09-14 DOI: 10.1080/03081079.2023.2256462
Dali Wang, Qingyuan Xu, Jinjin Li, Yongfan Zhu
AbstractInstructional assessment and learning paths are essential for improving students' learning effectiveness. This paper explores enhancing learners' learning efficiency and quality from the perspective of the correlation between skills. Firstly, the concept of the skill hierarchy structure and valid skill combination is introduced, followed introducted the method of constructing a question bank based on the skill hierarchy structure. Secondly, the skill hierarchy structure is utilized to induce skill context and provide the competence base for the skill context. Finally, the method for assessing the skills mastered by the learner is provided in the case of a known knowledge state of learners, and the learning paths diagram suitable for the learner's personalized situation is constructed. Experimental results demonstrate that the competence structure derived from the induced skill context based on skill hierarchy structure meets the requirements of being well-graded. Furthermore, the proposed methods in this paper facilitate learners in effectively mastering and applying learned skills, thereby establishing a solid foundation and improving their learning efficiency.KEYWORDS: Skill hierarchy structurevalid skill combinationskill contextcompetence baseskill assessmentlearning paths Disclosure statementNo potential conflict of interest was reported by the author(s).
摘要教学评价和学习路径是提高学生学习效率的关键。本文从技能相关性的角度探讨提高学习者的学习效率和学习质量。首先介绍了技能层次结构和有效技能组合的概念,然后介绍了基于技能层次结构构建题库的方法。其次,利用技能层次结构归纳技能语境,为技能语境提供能力基础;最后,给出了在学习者知识状态已知的情况下评估学习者掌握的技能的方法,并构建了适合学习者个性化情况的学习路径图。实验结果表明,从基于技能层次结构的诱导技能语境中得到的胜任力结构满足良好分级的要求。此外,本文提出的方法有助于学习者有效地掌握和应用所学的技能,从而奠定坚实的基础,提高学习效率。关键词:技能层次结构、有效技能组合、技能语境、能力基础、技能评估、学习路径披露声明作者未报告潜在的利益冲突。
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引用次数: 0
Attribute reduction for incomplete mixed data based on neighborhood information system 基于邻域信息系统的不完全混合数据属性约简
4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-09-12 DOI: 10.1080/03081079.2023.2256464
Ran Li, Hongchang Chen, Shuxin Liu, Haocong Jiang, Biao Wang
In an era of data-based and information-centric Industry 4.0, extracting potential knowledge and valuable information from data is central to data mining tasks. Yet, the ambiguity, imprecision, incompleteness, and hybrid in real-world data pose tremendous challenges to critical information mining. Accordingly, we propose a new Max-Correlation Min-Redundant (MCMR) attribute reduction model from the uncertainty relation of attributes to avoid information loss in incomplete mixed data. Specifically, the neighbor relations are primarily developed based on the soft computing approach of the neighborhood information system, which divides the objects into neighborhood covers to maximize the utilization of the information in the incomplete mixed data. Then, we detailly analyze the internal and external consistency relationships of the four main uncertainty functions. Based on this, a new MCMR uncertain function is designed with maximum relevance and minimum redundancy. Experiments on nine real-world datasets validate the proposed model can improve data quality by mining critical information in classification tasks and achieving optimal performance with a minimum number of attributes.
在以数据为基础、以信息为中心的工业4.0时代,从数据中提取潜在知识和有价值的信息是数据挖掘任务的核心。然而,现实世界数据的模糊性、不精确性、不完整性和混合性给关键信息挖掘带来了巨大的挑战。为此,从属性的不确定性关系出发,提出了一种新的最大相关最小冗余属性约简模型,以避免不完全混合数据中的信息丢失。具体来说,邻域关系主要是基于邻域信息系统的软计算方法开发的,邻域信息系统将对象划分为邻域覆盖,最大限度地利用不完全混合数据中的信息。然后,详细分析了四种主要不确定性函数的内外一致性关系。在此基础上,设计了一种关联度最大、冗余度最小的MCMR不确定函数。在9个真实数据集上的实验验证了该模型可以通过挖掘分类任务中的关键信息,以最少的属性数量实现最优性能,从而提高数据质量。
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引用次数: 0
On the concept of fuzzy order II: Antisymmetry 关于模糊序的概念II:反对称
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-08-31 DOI: 10.1080/03081079.2023.2232938
R. Belohlávek, Tomas Urbanec
In the second part of our paper, we explore antisymmetry of fuzzy orders. We provide a unifying definition of antisymmetry, which generalizes three existing variants of antisymmetry examined in the literature, along with the corresponding generalized definition of fuzzy order. We prove that all the particular instances of the generalized definition, which include the three basic ones, are mutually equivalent. We also examine distinctive properties of the three basic notions of fuzzy order.
在本文的第二部分,我们探讨了模糊序的反对称性。我们提供了反对称性的统一定义,它推广了文献中研究的三种现有的反对称性变体,以及相应的模糊序的广义定义。我们证明了广义定义的所有特定实例,包括三个基本实例,都是相互等价的。我们还考察了模糊序的三个基本概念的不同性质。
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引用次数: 2
On the concept of fuzzy order I: Remarks and observations 关于模糊序的概念I:注记与观察
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-08-31 DOI: 10.1080/03081079.2023.2232937
R. Belohlávek, Tomas Urbanec
We consider the concept of fuzzy order in which antisymmetry is intrinsically connected to a many-valued equality on the underlying universe. We examine the origins of this concept, provide remarks and observations on the existing studies, and prove new results. In part I, we scrutinize the existing approaches to the examined concept of fuzzy order and present remarks and results to elucidate the available notions and findings, as well as to provide a deeper insight into several issues. In part II, we explore antisymmetry.
我们考虑了模糊秩序的概念,在模糊秩序中,反对称性与底层宇宙上的多值等式本质上是联系在一起的。我们考察了这一概念的起源,对现有研究进行了评论和观察,并证明了新的结果。在第一部分中,我们仔细研究了模糊顺序概念的现有方法,并提出了评论和结果,以阐明现有的概念和发现,并对几个问题提供更深入的见解。在第二部分中,我们探讨了反对称性。
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引用次数: 2
p-Accelerated normal S-iterative learning control algorithm for linear discrete singular time-delay systems 线性离散奇异时滞系统的p加速正态s迭代学习控制算法
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-08-18 DOI: 10.1080/03081079.2023.2241982
D. R. Sahu, N. Singh
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引用次数: 0
Metamodel-based dynamic algorithm configuration using artificial neural networks 基于元模型的人工神经网络动态组态算法
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-08-16 DOI: 10.1080/03081079.2023.2245124
Fabian Dunke, S. Nickel
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引用次数: 0
On lacunary statistical convergence of double sequences in credibility theory 可信性理论中双序列的空缺统计收敛性
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-08-02 DOI: 10.1080/03081079.2023.2210742
R. Savaş, M. Gürdal
In 1951, the notion of statistical convergence was a more general concept than the idea of convergence as by presented by Fast. Since then statistical convergence has been was investigated by more and more researchers. On the other hand, in 2006 Li has began the survey of credibility theory and presented some convergence concepts in credibility theory. Because of the esoteric of both credibility and summability theory, the body of literature is limited. As such the only accessible notion to both theories is Pringsheim limits. The goal of this paper is to present a natural multidimensional extension of credibility theory via summability methods. To accomplish this, in this paper we present useful tools to generalize the well-known convergence definition to the concept of lacunary statistical convergence for double sequences in credibility theory. Additionally, some important results and examples will be examined.
在1951年,统计收敛的概念是一个比Fast提出的收敛概念更普遍的概念。此后,越来越多的研究者开始研究统计收敛问题。另一方面,李在2006年开始了对可信度理论的调查,并提出了可信度理论中的一些收敛概念。由于可信性理论和可归纳性理论的深奥性,文献主体受到了限制。因此,两种理论唯一可以理解的概念是普林斯海姆极限。本文的目的是通过可和性方法对可信度理论进行自然的多维扩展。为了实现这一点,本文给出了一些有用的工具,将众所周知的收敛定义推广到可信性理论中双序列的空白统计收敛概念。此外,一些重要的结果和例子将被检查。
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引用次数: 0
General power laws of the causalities in the causal Bayesian networks 因果贝叶斯网络中因果关系的一般幂律
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-07-19 DOI: 10.1080/03081079.2023.2234076
Boyuan Li, Xiaoyang Li, Zhaoxing Tian, Xia Lu, Rui Kang
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引用次数: 0
Discovering overlapping communities using a new diffusion approach based on core expanding and local depth traveling in social networks 基于社交网络核心扩展和局部深度旅行的新扩散方法发现重叠社区
IF 2 4区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS Pub Date : 2023-07-16 DOI: 10.1080/03081079.2023.2233050
Asgarali Bouyer, Maryam Sabavand Monfared, E. Nourani, Bahman Arasteh
This paper proposes a local diffusion-based approach to find overlapping communities in social networks based on label expansion using local depth first search and social influence information of nodes, called the LDLF algorithm. It is vital to start the diffusion process in local depth, traveling from specific core nodes based on their local topological features and strategic position for spreading community labels. Correspondingly, to avoid assigning excessive and unessential labels, the LDLF algorithm prudently removes redundant and less frequent labels for nodes with multiple labels. Finally, the proposed method finalizes the node's label based on the Hub Depressed index. Thanks to requiring only two iterations for label updating, the proposed LDLF algorithm runs in low time complexity while eliminating random behavior and achieving acceptable accuracy in finding overlapping communities for large-scale networks. The experiments on benchmark networks prove the effectiveness of the LDLF method compared to state-of-the-art approaches.
本文提出了一种基于局部扩散的基于标签扩展的方法,利用局部深度优先搜索和节点的社会影响信息来寻找社会网络中的重叠社区,称为LDLF算法。从特定的核心节点开始,根据其局部拓扑特征和战略位置,从局部深度开始扩散过程,以传播社区标签是至关重要的。相应的,为了避免分配过多和不必要的标签,LDLF算法会对具有多个标签的节点谨慎地去除冗余和不太频繁的标签。最后,该方法基于Hub消沉索引最终确定节点的标签。由于标签更新只需要两次迭代,所提出的LDLF算法在低时间复杂度下运行,同时消除了随机行为,并且在大规模网络中找到重叠社区时达到了可接受的精度。在基准网络上的实验证明了该方法的有效性。
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International Journal of General Systems
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