INTERVAL METHODS IN KNOWLEDGE REPRESENTATION (Abstracts of recent papers)

VLADIK KREINOVICH

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INTERVAL METHODS IN KNOWLEDGE REPRESENTATION (Abstracts of recent papers)

机译：知识表示的区间方法（最新论文摘要）

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A fuzzy interval is defined as a fuzzy set on the real line for which all α-cuts are intervals; in particular, every interval is a particular case of a fuzzy interval. This paper is a survey on fuzzy intervals, operations on them, fuzzy interval equations, and applications of fuzzy intervals.

机译：模糊区间被定义为所有α割都是区间的实线上的模糊集。特别地，每个间隔是模糊间隔的特定情况。本文对模糊区间，模糊区间的运算，模糊区间方程以及模糊区间的应用进行了概述。

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《International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems》 |2000年第5期|p.619-620|共2页
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VLADIK KREINOVICH;
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正文语种 eng
中图分类计算技术、计算机技术;
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1. INTERVAL METHODS IN KNOWLEDGE REPRESENTATION (Abstracts of recent papers) [J] . VLADIK KREINOVICH International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems . 2001,第4期

机译：知识表示的区间方法（最新论文摘要）
2. INTERVAL METHODS IN KNOWLEDGE REPRESENTATION (Abstract of recent papers) [J] . VLADIK KREINOVICH International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems . 2000,第3期

机译：知识表示的区间方法（最新论文摘要）
3. Interval Methods in Knowledge Representation [J] . Kreinovich Vladik International journal of uncertainty, fuzziness and knowledge-based systems . 2021,第4期

机译：知识表示中的间隔方法
4. Comparison of the nodes of knowledge method with other graphical methods for knowledge representation [C] . Jakupovic Alen, Pavlic Mile, Mestrovic Ana, International Convention on Information and Communication Technology, Electronics and Microelectronics . 2013

机译：知识方法的节点与其他图形表示方法的比较
5. Effects of abstract versus concrete visual representations in an instructional simulation on students' declarative knowledge, learning transfer, and perceptions of the simulation. [D] . Mejia, William Ernesto. 2011

机译：教学模拟中的抽象视觉表示与具体视觉表示对学生的陈述性知识，学习转移和对模拟的感知的影响。
6. Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level [O] . Loet Leydesdorff, Jordan A. Comins, Aaron A. Sorensen, -1

机译：被引用的参考文献和医学主题词（MeSH）是两种不同的知识表示形式：论文层面的聚类和映射
7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

INTERVAL METHODS IN KNOWLEDGE REPRESENTATION (Abstracts of recent papers)

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