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Relevant bibliographies by topics / Interval computing

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Academic literature on the topic 'Interval computing'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Interval computing"

1

Kleitman, Daniel J., and Rakesh V. Vohra. "Computing the Bandwidth of Interval Graphs." SIAM Journal on Discrete Mathematics 3, no. 3 (1990): 373–75. http://dx.doi.org/10.1137/0403033.

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Galbraith, Steven D., John M. Pollard, and Raminder S. Ruprai. "Computing discrete logarithms in an interval." Mathematics of Computation 82, no. 282 (2012): 1181–95. http://dx.doi.org/10.1090/s0025-5718-2012-02641-x.

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Kim, Minkyu, and Jung Hee Cheon. "Computing prime divisors in an interval." Mathematics of Computation 84, no. 291 (2014): 339–54. http://dx.doi.org/10.1090/s0025-5718-2014-02840-8.

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Kloks, Ton, Jan Kratochvíl, and Haiko Müller. "Computing the branchwidth of interval graphs." Discrete Applied Mathematics 145, no. 2 (2005): 266–75. http://dx.doi.org/10.1016/j.dam.2004.01.015.

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Maier, R. W., J. F. Brennecke, and M. A. Stadtherr. "Computing Homogeneous Azeotropes Using Interval Analysis." Chemical Engineering & Technology 22, no. 12 (1999): 1063–67. http://dx.doi.org/10.1002/(sici)1521-4125(199912)22:12<1063::aid-ceat1063>3.0.co;2-z.

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Nagy, Benedek, and Sándor Vályi. "Circular Interval-valued Computers and Simulation of (Red-green) Turing Machines." Fundamenta Informaticae 181, no. 2-3 (2021): 213–38. http://dx.doi.org/10.3233/fi-2021-2057.

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Interval-valued computing is a kind of massively parallel computing. It operates on specific subsets of the interval [0,1) – unions of subintervals. They serve as basic data units and are called interval-values. It was established in [9], by a rather simple observation, that interval-valued computing, as a digital computing model, has computing power equivalent to Turing machines. However, this equivalence involves an unlimited number of interval-valued variables. In [14], the equivalence with Turing machines is established using a simulation that uses only a fixed number of interval-valued va

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Senn, Christoph Walter, and Itsuo Kumazawa. "Abstract Reservoir Computing." AI 3, no. 1 (2022): 194–210. http://dx.doi.org/10.3390/ai3010012.

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Noise of any kind can be an issue when translating results from simulations to the real world. We suddenly have to deal with building tolerances, faulty sensors, or just noisy sensor readings. This is especially evident in systems with many free parameters, such as the ones used in physical reservoir computing. By abstracting away these kinds of noise sources using intervals, we derive a regularized training regime for reservoir computing using sets of possible reservoir states. Numerical simulations are used to show the effectiveness of our approach against different sources of errors that ca

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Gillner, Lorenz, and Ekaterina Auer. "GPU-Accelerated, Interval-Based Parameter Identification Methods Illustrated Using the Two-Compartment Problem." Acta Cybernetica 26, no. 4 (2024): 913–32. https://doi.org/10.14232/actacyb.306774.

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Interval methods are helpful in the context of scientific computing for reliable treatment of problems with bounded uncertainty. Most traditional interval algorithms, however, were designed for sequential execution while internally depending on processor-specific instructions for directed rounding. Nowadays, many-core processors and dedicated hardware for massively parallel data processing have become the de facto standard for high-performance computers. Interval libraries have yet to adapt to this heterogeneous computing paradigm. In this article, we investigate the parallelization of interva

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Guan, Qing, and Jian He Guan. "Knowledge Acquisition of Interval Set-Valued Based on Granular Computing." Applied Mechanics and Materials 543-547 (March 2014): 2017–23. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2017.

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The technique of a new extension of fuzzy rough theory using partition of interval set-valued is proposed for granular computing during knowledge discovery in this paper. The natural intervals of attribute values in decision system to be transformed into multiple sub-interval of [0,1]are given by normalization. And some characteristics of interval set-valued of decision systems in fuzzy rough set theory are discussed. The correctness and effectiveness of the approach are shown in experiments. The approach presented in this paper can also be used as a data preprocessing step for other symbolic

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Bustince, Humberto. "Interval-valued Fuzzy Sets in Soft Computing." International Journal of Computational Intelligence Systems 3, no. 2 (2010): 215. http://dx.doi.org/10.2991/ijcis.2010.3.2.9.

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Dissertations / Theses on the topic "Interval computing"

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Ramadoss, Revathy Carleton University Dissertation Engineering Systems and Computer. "Interval-based performance analysis of computing systems." Ottawa, 1994.

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Wang, Haibin. "Interval neutrosophic sets and logic theory and applications in computing /." unrestricted, 2005. http://etd.gsu.edu/theses/available/etd-11172005-131340/.

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Thesis (Ph. D.)--Georgia State University, 2005.<br>1 electronic text (119 p. : ill.) : digital, PDF file. Title from title screen. Rajshekhar Sunderraman, committee chair; Yan-Qing Zhang, Anu Bourgeois, Lifeng Ding, committee members. Description based on contents viewed Apr. 3, 2007. Includes bibliographical references (p. 112-119).

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Wang, Haibin. "Interval Neutrosophic Sets and Logic: Theory and Applications in Computing." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_diss/2.

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A neutrosophic set is a part of neutrosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a powerful general formal framework that has been recently proposed. However, the neutrosophic set needs to be specified from a technical point of view. Here, we define the set-theoretic operators on an instance of a neutrosophic set, and call it an Interval Neutrosophic Set (INS). We prove various properties of INS, which are connected to operations and relations over INS. We also introduce a new logic

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Nguyen, Hong Diep. "Efficient algorithms for verified scientific computing : Numerical linear algebra using interval arithmetic." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2011. http://tel.archives-ouvertes.fr/tel-00680352.

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Interval arithmetic is a means to compute verified results. However, a naive use of interval arithmetic does not provide accurate enclosures of the exact results. Moreover, interval arithmetic computations can be time-consuming. We propose several accurate algorithms and efficient implementations in verified linear algebra using interval arithmetic. Two fundamental problems are addressed, namely the multiplication of interval matrices and the verification of a floating-point solution of a linear system. For the first problem, we propose two algorithms which offer new tradeoffs between speed an

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Zhao, Chenyuan. "Spike Processing Circuit Design for Neuromorphic Computing." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/93591.

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Von Neumann Bottleneck, which refers to the limited throughput between the CPU and memory, has already become the major factor hindering the technical advances of computing systems. In recent years, neuromorphic systems started to gain increasing attention as compact and energy-efficient computing platforms. Spike based-neuromorphic computing systems require high performance and low power neural encoder and decoder to emulate the spiking behavior of neurons. These two spike-analog signals converting interface determine the whole spiking neuromorphic computing system's performance, especially t

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Kazazakis, Nikolaos. "Parallel computing, interval derivative methods, heuristic algorithms, and their implementation in a numerical solver, for deterministic global optimization." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/45359.

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This thesis presents new algorithms for the deterministic global optimization of general non-linear programming problems (NLPs). It is proven that the αBB general underestimator may provide exact lower bounds on a function only if rigorous conditions are satisfied. These conditions are derived and the μ-subenergy methodology is proposed to achieve tighter αBB underestimation when they are violated. An interval lower bounding test is proposed to improve αBB lower bounds and avoid expensive algorithmic steps. Piecewise-linear relaxations (PLR) are proposed for the underestimation of general func

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Xiang, Gang. "Fast algorithms for computing statistics under interval uncertainty with applications to computer science and to electrical and computer engineering /." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2007. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Phithakkitnukoon, Santi Dantu Ram. "Inferring social and internal context using a mobile phone." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12183.

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Phithakkitnukoon, Santi. "Inferring Social and Internal Context Using a Mobile Phone." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12183/.

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This dissertation is composed of research studies that contribute to three research areas including social context-aware computing, internal context-aware computing, and human behavioral data mining. In social context-aware computing, four studies are conducted. First, mobile phone user calling behavioral patterns are characterized in forms of randomness level where relationships among them are then identified. Next, a study is conducted to investigate the relationship between the calling behavior and organizational groups. Third, a method is presented to quantitatively define mobile social cl

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Jin, Shaobo. "Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions." Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-200550.

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Books on the topic "Interval computing"

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Krämer, Walter, and Jürgen Wolff von Gudenberg, eds. Scientific Computing, Validated Numerics, Interval Methods. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-6484-0.

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Krämer, Walter. Scientific Computing, Validated Numerics, Interval Methods. Springer US, 2001.

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Walter, Krämer, and Gudenberg, J. Wolff von 1952-, eds. Scientific computing, validated numerics, interval methods. Kluwer Academic/Plenum, 2001.

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Kreinovich, Vladik, Andre Korvin, R. Baker Kearfott, and Chenyi Hu, eds. Knowledge Processing with Interval and Soft Computing. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-326-2.

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Nguyen, Hung T., Vladik Kreinovich, Berlin Wu, and Gang Xiang. Computing Statistics under Interval and Fuzzy Uncertainty. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24905-1.

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Chenyi, Hu, ed. Knowledge processing with interval and soft computing. Springer, 2008.

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Chenyi, Hu, ed. Knowledge processing with interval and soft computing. Springer, 2008.

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E, Moore Ramon, ed. Reliability in computing: The role of interval methods in scientific computing. Academic Press, 1988.

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9

Vladik, Kreinovich, University of Texas at El Paso. Institute for Manufacturing and Materials Management., and International Workshop on Applications of Interval Computations (1995 : El Paso, Tex.), eds. International journal of Reliable computing =: Formerly Interval computations. University of Texas at El Paso, Institute for Manufacturing and Materials Management, 1995.

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Van-Nam, Huynh, ed. Interval/probabilistic uncertainty and non-classical logics. Springer, 2008.

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Book chapters on the topic "Interval computing"

1

Kearfott, Ralph Baker. "Interval Computing." In Encyclopedia of Complexity and Systems Science Series. Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-2628-3_722.

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Kearfott, Ralph Baker. "Interval Computing." In Encyclopedia of Complexity and Systems Science. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27737-5_722-1.

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Rokne, Jon G. "Interval Arithmetic and Interval Analysis: An Introduction." In Granular Computing. Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1823-9_1.

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Kearfott, Ralph Baker, and Chenyi Hu. "Fundamentals of Interval Computing." In Advanced Information and Knowledge Processing. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-326-2_1.

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Lerch, Michael, and Jürgen Wolff Von Gudenberg. "Multiaspect Interval Types." In Developments in Reliable Computing. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-017-1247-7_29.

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Rump, Siegfried M. "INTLAB — INTerval LABoratory." In Developments in Reliable Computing. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-017-1247-7_7.

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Chakraverty, Snehashish, Deepti Moyi Sahoo, and Nisha Rani Mahato. "Interval Eigenvalue Problems." In Concepts of Soft Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7430-2_9.

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Kreinovich, Vladik. "Relations Between Interval Computing and Soft Computing." In Advanced Information and Knowledge Processing. Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-326-2_3.

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Pedrycz, Witold. "Interval Calculus." In An Introduction to Computing with Fuzzy Sets. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52800-3_3.

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Frommer, A., and G. Mayer. "Two-Stage Interval Iterative Methods." In Computing Supplementum. Springer Vienna, 1993. http://dx.doi.org/10.1007/978-3-7091-6918-6_5.

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Conference papers on the topic "Interval computing"

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Zhu, Chenyu, Kai Long, Lai Wei, and Zhixiong Ma. "Intelligent Driving Perception Interval Labelling Algorithm." In 2024 IEEE 6th International Conference on Power, Intelligent Computing and Systems (ICPICS). IEEE, 2024. https://doi.org/10.1109/icpics62053.2024.10796105.

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Nagy, Benedek. "Effective computing by interval-values." In 2010 IEEE 14th International Conference on Intelligent Engineering Systems. IEEE, 2010. http://dx.doi.org/10.1109/ines.2010.5483868.

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Lin, Tsau Young. "Approximate Computing in Numerical Analysis Variable Interval Computing - Extended Abstract." In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8914149.

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Sarmah, Naba Jyoti, and Anjana Kakoti Mahanta. "An incremental approach for mining all closed intervals from an interval database." In 2014 IEEE International Advance Computing Conference (IACC). IEEE, 2014. http://dx.doi.org/10.1109/iadcc.2014.6779380.

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Li, Qiaoxing. "The Interval Elementary Dependent Function Based on Interval Side-Distance." In 2008 ISECS International Colloquium on Computing, Communication, Control, and Management. IEEE, 2008. http://dx.doi.org/10.1109/cccm.2008.345.

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Nagy, Benedek, and S. Roland Major. "Connection between interval-valued computing and cellular automata." In 2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI). IEEE, 2013. http://dx.doi.org/10.1109/cinti.2013.6705196.

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Tzong-Wann Kao, Tzong-Wann Kao, and Shi-Jinn Horng Shi-Jinn Horng. "Computing k-Vertex Connectivity on an Interval Graph." In 1994 International Conference on Parallel Processing Vol. 3. IEEE, 1994. http://dx.doi.org/10.1109/icpp.1994.74.

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Pujara, L. R., and A. Roy. "On computing stabilizing controllers for SISO interval plants." In Proceedings of American Control Conference. IEEE, 2001. http://dx.doi.org/10.1109/acc.2001.946254.

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Bailey, F. N., and D. Panzer. "A Fast Algorithm for Computing Interval Rational Functions." In 1988 American Control Conference. IEEE, 1988. http://dx.doi.org/10.23919/acc.1988.4789684.

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Chuang, Chen-Chia, Chin-Wen Li, Chih-Ching Hsiao, Shun-Feng Su, and Jin-Tsong Jeng. "Robust interval support vector interval regression networks for interval-valued data with outliers." In 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2014. http://dx.doi.org/10.1109/scis-isis.2014.7044510.

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Reports on the topic "Interval computing"

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Som, Sibendu. Simulation of Internal Combustion Engines with High-Performance Computing Tools. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1337938.

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Romine, C. H., and B. W. Peyton. Computing connection coefficients of compactly supported wavelets on bounded intervals. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/661583.

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Woodruff, David L., and Jean-Paul Watson. Computing confidence intervals on solution costs for stochastic grid generation expansion problems. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1011614.

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Goldak, J. L51647 Welding on Fluid Filled and Pressurized Pipelines-Transient 3D Analysis. Pipeline Research Council International, Inc. (PRCI), 2000. http://dx.doi.org/10.55274/r0011356.

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The objective of this project was to determine if research in Computational Weld Mechanics had matured to the stage where it could simulate the process of welding on a pressurized pipeline and provide useful estimates of the risk of burn-through. To achieve that objective we have compared the results of our FEM analyzes of several welds with the experimental data reported in "http://www.prci.com/publications/L51763.htm" PR-185-9515, Repair of Pipelines by Direct Deposition of Weld Metal: Further Studies. The temperature and deformation predicted by our FEM analysis agrees quite well with the e

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Kondratenko, Larysa O., Hanna T. Samoylenko, Arnold E. Kiv, et al. Computer simulation of processes that influence adolescent learning motivation. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4452.

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In order for the learning process to always retain personal value for the learner, it is necessary that his or her motivation be maintained through an awareness of his or her purpose and goals. This article presents a local model (at the individual object level) of enhancing external motivation, which give to determine students’ efforts to get rewards. The concept of this model based on describing the behavior of agents (in our case students). The characteristics of the phenomenon in the motivation of learning at different stages of adolescent development are analyzed. The problem of computer

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Bauer, Andrew, James Forsythe, Jayanarayanan Sitaraman, Andrew Wissink, Buvana Jayaraman, and Robert Haehnel. In situ analysis and visualization to enable better workflows with CREATE-AV™ Helios. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40846.

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The CREATE-AV™ Helios CFD simulation code has been used to accurately predict rotorcraft performance under a variety of flight conditions. The Helios package contains a suite of tools that contain almost the entire set of functionality needed for a variety of workflows. These workflows include tools customized to properly specify many in situ analysis and visualization capabilities appropriate for rotorcraft analysis. In situ is the process of computing analysis and visualization information during a simulation run before data is saved to disk. In situ has been referred to with a variety of te

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