Relevant bibliographies by topics / Algorithm performance

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Algorithm performance'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Algorithm performance"

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Mary, A. Viji Amutha, and Dr T. Jebarajan Dr. T. Jebarajan. "Performance Metrics of Clustering Algorithm." Indian Journal of Applied Research 4, no. 8 (2011): 165–67. http://dx.doi.org/10.15373/2249555x/august2014/47.

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Han, Xiaofeng, Xuejia Qi, Jincheng Zhang, Songlin Yang, and Shuling Chen. "The Analysis Method of Performance Comprehensive Performance Optimization Design for Multi-body Unmanned Boat." Journal of Physics: Conference Series 2219, no. 1 (2022): 012048. http://dx.doi.org/10.1088/1742-6596/2219/1/012048.

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Abstract In order to compare and analyze the comprehensive performance of multi-hull unmanned boats under specific conditions, this paper conducts in-depth research on the multi-objective decision-making theory and intelligent optimization algorithms of boat type design. First of all, this paper establishes the corresponding ship type and resistance database using the response surface fitting method through the drag resistance test of the ship model. Secondly, comprehensively considering the impact of the three major performances of multi-hull unmanned craft on the design of the boat’s speed,
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Qiu, Jian Lin, Li Chen, Jian Ping Chen, Xiang Gu, and Yan Yun Chen. "Grid-Based Task Scheduling PMTS Algorithm." Applied Mechanics and Materials 121-126 (October 2011): 4491–97. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.4491.

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This paper analyses the Min-min algorithm and its improved algorithms through the performances of load balance, time span, quality of service and economic principle. Based on the analysis of the merits of these algorithms, we propose an improved algorithm as PMTS (Priority-based maximum time-span algorithm) by integrating. In the instance of the application, we analyse and compare the performances of these algorithms, and experimental results show that, PMTS algorithm is better than other algorithms in the comprehensive performance of load-balance, time-span, quality of service and other aspec
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Civicioglu, P., U. H. Atasever, C. Ozkan, E. Besdok, A. E. Karkinli, and A. Kesikoglu. "Performance Comparison Of Evolutionary Algorithms For Image Clustering." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7 (September 19, 2014): 71–74. http://dx.doi.org/10.5194/isprsarchives-xl-7-71-2014.

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Evolutionary computation tools are able to process real valued numerical sets in order to extract suboptimal solution of designed problem. Data clustering algorithms have been intensively used for image segmentation in remote sensing applications. Despite of wide usage of evolutionary algorithms on data clustering, their clustering performances have been scarcely studied by using clustering validation indexes. In this paper, the recently proposed evolutionary algorithms (i.e., Artificial Bee Colony Algorithm (ABC), Gravitational Search Algorithm (GSA), Cuckoo Search Algorithm (CS), Adaptive Di
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Kaur, Baljit. "Performance Comparison between LMS and NLMS Algorithm." Indian Journal of Applied Research 1, no. 6 (2011): 63–65. http://dx.doi.org/10.15373/2249555x/mar2012/20.

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Saini, Deepali, and Prof Anand Rajavat. "Performance Evaluation System for Decision Tree Algorithms." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 8 (2013): 2879–86. http://dx.doi.org/10.24297/ijct.v11i8.3006.

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In the machine learning process, classification can be described by supervise learning algorithm. Classification techniques have properties that enable the representation of structures that reflect knowledge of the domain being classified. Industries, education, business and many other domains required knowledge for the growth. Some of the common classification algorithms used in data mining and decision support systems is: Neural networks, Logistic regression, Decision trees etc. The decision regarding most suitable data mining algorithm cannot be made spontaneously. Selection of appropriate
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YE, DESHI, and QINMING HE. "WORST-CASE PERFORMANCE EVALUATION ON MULTIPROCESSOR TASK SCHEDULING WITH RESOURCE AUGMENTATION." International Journal of Foundations of Computer Science 22, no. 04 (2011): 971–82. http://dx.doi.org/10.1142/s0129054111008519.

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We study the worst-case performance of approximation algorithms for the problem of multiprocessor task scheduling on m identical processors with resource augmentation, whose objective is to minimize the makespan. In this case, the approximation algorithms are given k (k ≥ 0) extra processors than the optimal off-line algorithm. For on-line algorithms, the Greedy algorithm and shelf algorithms are studied. For off-line algorithm, we consider the LPT (longest processing time) algorithm. Particularly, we prove that the schedule produced by the LPT algorithm is no longer than the optimal off-line
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Zhang, Qingyang, Tianji Peng, Guangchun Zhang, et al. "An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing." Science and Technology of Nuclear Installations 2021 (September 24, 2021): 1–16. http://dx.doi.org/10.1155/2021/5549602.

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This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel a
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Qiu, Dong Wei, and Shan Shan Wan. "Research on Algorithms Performance about JSP Scheduling." Advanced Materials Research 457-458 (January 2012): 20–25. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.20.

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Three typical intelligent evolutionary algorithms are applied on Job Shop scheduling problem which are Quantum algorithm, Genetic Algorithm and Population Based Incremental Learning algorithm. They three algorithms have some common features in computation, encoding strategy and probability application, but with the different problems and different scale sizes of the same problem they show different performance. In this paper we take JSP as example to test their performance difference and analyze their applicability. Two benchmark Job Shop problems are used to fulfill the comparison. The result
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Ozkan, Ramazan, and Ruya Samli. "Flood algorithm: a novel metaheuristic algorithm for optimization problems." PeerJ Computer Science 10 (October 2, 2024): e2278. http://dx.doi.org/10.7717/peerj-cs.2278.

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Metaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods. Since the performances of these algorithms vary for different types of problems, many studies have been and need to be done to propose different metaheuristic algorithms. In this article, a new metaheuristic algorithm called flood algorithm (FA) is proposed for optimization problems. It is inspired by the flow of flood water on the earth’s surface. The proposed algorithm is tested both on benchmark functions and on a real-world p
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Dissertations / Theses on the topic "Algorithm performance"

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Wang, Lingyun. "Feeder Performance Analysis with Distributed Algorithm." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/31949.

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How to evaluate the performance of an electric power distribution system unambiguously and quantitatively is not easy. How to accurately measure the efficiency of it for a whole year, using real time hour-by-hour Locational Marginal Price data, is difficult. How to utilize distributed computing technology to accomplish these tasks with a timely fashion is challenging. This thesis addresses the issues mentioned above, by investigating feeder performance analysis of electric power distribution systems with distributed algorithm. Feeder performance analysis computes a modeled circuitâ s perfor
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Pochet, Juliette. "Evaluation de performance d’une ligne ferroviaire suburbaine partiellement équipée d’un automatisme CBTC." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLC005.

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En zone dense, la croissance actuelle du trafic sur les lignes ferroviaires suburbaines conduit les exploitants à déployer des systèmes de contrôle-commande avancés des trains, tels que les systèmes dits « CBTC » (Communication Based Train Control) jusque-là réservés aux systèmes de métro. Les systèmes CBTC mettent en œuvre un pilotage automatique des trains et permettent une amélioration significative des performances. Par ailleurs, ils peuvent inclure un module de supervision de la ligne en charge de réguler la marche des trains en cas d’aléa, améliorant ainsi la robustesse du trafic. Face a
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Hamrin, Niklas, and Nils Runebjörk. "Examining Sorting Algorithm Performance Under System Load." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209765.

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In this thesis, we conducted tests in order to determine how system load affected the speed of commonly used algorithms. The difficulty of obtaining these type of results theoretically due to a large number of factors that can affect performance motivated the use of simulation. An implementation was constructed that ran the sorting algorithms Mergesort, Quicksort and Radixsort while the system was put under different levels of stress. This stress was created by generating cache misses using the software stress-ng. The resulting completion times, as well as the cache activity was logged. The re
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Musselman, Roger D. "Robustness a better measure of algorithm performance." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Sep%5FMusselman.pdf.

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2007.<br>Thesis Advisor(s): Sanchez, Paul J. "September 2007." Description based on title screen as viewed on October 25, 2007. Includes bibliographical references (p. 55-56). Also available in print.
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Chu, Yijing, and 褚轶景. "Resursive local estimation: algorithm, performance and applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B49799320.

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Adaptive filters are frequently employed in many applications, such as, system identification, adaptive echo cancellation (AEC), active noise control (ANC), adaptive beamforming, speech signal processing and other related problems, in which the statistic of the underlying signals is either unknown a priori, or slowly-varying. Given the observed signals under study, we shall consider, in this dissertation, the time-varying linear model with Gaussian or contaminated Gaussian (CG) noises. In particular, we focus on recursive local estimation and its applications in linear systems. We base our
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Jonas, Mario Ricardo Edward. "High performance computing and algorithm development: application of dataset development to algorithm parameterization." Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&amp.

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A number of technologies exist that captures data from biological systems. In addition, several computational tools, which aim to organize the data resulting from these technologies, have been created. The ability of these tools to organize the information into biologically meaningful results, however, needs to be stringently tested. The research contained herein focuses on data produced by technology that records short Expressed Sequence Tags (EST's).
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Anderson, Roger J. "Characterization of Performance, Robustness, and Behavior Relationships in a Directly Connected Material Handling System." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/26967.

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In the design of material handling systems with complex and unpredictable dynamics, conventional search and optimization approaches that are based only on performance measures offer little guarantee of robustness. Using evidence from research into complex systems, the use of behavior-based optimization is proposed, which takes advantage of observed relationships between complexity and optimality with respect to both performance and robustness. Based on theoretical complexity measures, particularly algorithmic complexity, several simple complexity measures are created. The relationships betw
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Li, Chuhe. "A sliding window BIRCH algorithm with performance evaluations." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-32397.

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An increasing number of applications covered various fields generate transactional data or other time-stamped data which all belongs to time series data. Time series data mining is a popular topic in the data mining field, it introduces some challenges to improve accuracy and efficiency of algorithms for time series data. Time series data are dynamical, large-scale and high complexity, which makes it difficult to discover patterns among time series data with common methods suitable for static data. One of hierarchical-based clustering methods called BIRCH was proposed and employed for addressi
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Martins, Wellington Santos. "Algorithm performance on a general purpose parallel computer." Thesis, University of East Anglia, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296870.

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Balasubramanian, Priya. "Interfacing VHDL performance models to algorithm partitioning tools." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-02132009-172459/.

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Books on the topic "Algorithm performance"

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H, Lambert Heather, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Preliminary flight evaluation of an engine performance optimization algorithm. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1991.

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Dunn, Ian N., and Gerard G. L. Meyer. A Parallel Algorithm Synthesis Procedure for High-Performance Computer Architectures. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-8650-4.

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L, Meyer Gerard G., ed. A parallel algorithm synthesis procedure for high-performance computer architectures. Kluwer Academic/Plenum Publishers, 2003.

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Dunn, Ian N. A Parallel Algorithm Synthesis Procedure for High-Performance Computer Architectures. Springer US, 2003.

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Smart, John R. Performance evaluation of the NEXRAD Hail Algorithm applied to Colorado thunderstorms. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1985.

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Orme, John S. Flight assessment of the onboard propulsion system for the performance seeking control algorithm on an F-15 aircraft. Dryden Flight Research Center, 1995.

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Kobayashi, Takahisa. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. National Aeronautics and Space Administration, Glenn Research Center, 2001.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., ed. On the estimation algorithm used in adaptive performance optimization of turbofan engines. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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T, Nguyen Duc, Agarwal Tarun K, and Langley Research Center, eds. A parallel-vector algorithm for rapid structural analysis on high-performance computers. National Aeronautics and Space Administration, Langley Research Center, 1990.

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Kobayashi, Takahisa. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. National Aeronautics and Space Administration, Glenn Research Center, 2001.

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Book chapters on the topic "Algorithm performance"

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Mantaci, Roberto, and Jean-Baptiste Yunès. "Algorithm Performance." In Basics of Programming and Algorithms, Principles and Applications. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59801-2_7.

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Goldshtein, Sasha, Dima Zurbalev, and Ido Flatow. "Algorithm Optimization." In Pro .NET Performance. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4459-2_9.

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Bojesen, Jesper, Jyrki Katajainen, and Maz Spork. "Performance Engineering Case Study: Heap Construction." In Algorithm Engineering. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48318-7_24.

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Ewald, Roland. "Simulation Algorithm Performance Analysis." In Automatic Algorithm Selection for Complex Simulation Problems. Vieweg+Teubner Verlag, 2012. http://dx.doi.org/10.1007/978-3-8348-8151-9_3.

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Hanke, Sabine. "The Performance of Concurrent Red-Black Tree Algorithms." In Algorithm Engineering. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48318-7_23.

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Fourneau, J. M., and L. Mokdad. "A Perturbation and Reduction Based Algorithm." In Computer Performance Evaluation. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-68061-6_12.

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Bilardi, Gianfranco, Paolo D’Alberto, and Alex Nicolau. "Fractal Matrix Multiplication: A Case Study on Portability of Cache Performance." In Algorithm Engineering. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44688-5_3.

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Roe, Michael, Wei Xu, and Dongping Song. "Evaluating the Multiple Objective Genetic Algorithm." In Optimizing Supply Chain Performance. Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137501158_10.

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Roe, Michael, Wei Xu, and Dongping Song. "Evaluating the Single Objective Genetic Algorithm." In Optimizing Supply Chain Performance. Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137501158_9.

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Tewari, Ambuj, Utkarsh Srivastava, and P. Gupta. "A Parallel DFA Minimization Algorithm." In High Performance Computing — HiPC 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36265-7_4.

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Conference papers on the topic "Algorithm performance"

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Jencka, Louis, and Amanda Bienz. "Compressed Cannon's Algorithm." In 2024 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2024. https://doi.org/10.1109/hpec62836.2024.10938440.

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Zhao, Ruiting, Jingru Ding, Tianqi Song, and Anqi Ye. "Multi-algorithm comparison and performance evaluation." In International Conference on Cloud Computing, Performance Computing, and Deep Learning, edited by Wanyang Dai and Xiangjie Kong. SPIE, 2024. http://dx.doi.org/10.1117/12.3050805.

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Huang, Xueyu, and Jinwei Yi. "Fusion strategy-driven dung beetle optimization algorithm." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051352.

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Chi, Dianwei, Zehao Jia, Tiantian Huang, et al. "An improvement of a decision tree ID3 algorithm." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051346.

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Yong, Gao, Wang Zhigang, Li Hengwu, Guo Hui, and Zhao Liang. "Blockchain signature acceleration engine based on SM2 algorithm." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051327.

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yang, zhenhu, Ning Hu, and Lei Zhou. "An efficient multi-step parallel FFT algorithm on GPU." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051802.

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Chen, Dawei, and Lu Yuan. "Federated learning with improved aggregation via optimal transport algorithm." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051407.

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Mu, Zhilin, Xin Sun, and Tiande Guo. "A fast algorithm for maximizing monotone non-submodular functions." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051434.

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Shen, Hongping, and Ling Wu. "Research on building optimization design based on genetic algorithm." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051667.

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Liu, Tao, and Xiaohui Huang. "Apple surface defect detection algorithm based on improved YOLOv8." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051665.

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Reports on the topic "Algorithm performance"

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Thompson, David C., and Philippe Pierre Pebay. Performance of a streaming mesh refinement algorithm. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/919132.

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Mustacich, Robert V., William Foreman, and Paul M. Holland. Task 2 Report: Algorithm Development and Performance Analysis. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/adb174940.

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Carrano, C. Bispectral Speckle Imaging Algorithm Performance on Specific Simulated Scenarios. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1108864.

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Vouras, Peter G., and Gerard G. L. Meyer. Hybrid QR Factorization Algorithm for High Performance Computing Architectures. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada419390.

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Jimoh, Mujeeb B. Performance Testing of GPU-Based Approximate Matching Algorithm on Network Traffic. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada620807.

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Peeta, Srinivas, Amit Kumar, and Sushant Sharma. Post-Processing Techniques to Enhance Reliability of Assignment Algorithm Based Performance Measures. Purdue University, 2011. http://dx.doi.org/10.5703/1288284314643.

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Milora, S. L., S. K. Combs, M. J. Gouge, and R. W. Kincaid. QUICKGUN: An algorithm for estimating the performance of two-stage light gas guns. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6428575.

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Sun, Xiaobai, and Nikos P. Pitsianis. FANTOM: Algorithm-Architecture Codesign for High-Performance Embedded Signal and Image Processing Systems. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada581464.

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Dahlgren, Kathryn Marie, Francesco Rizzi, Karla Vanessa Morris, and Bert Debusschere. Rexsss Performance Analysis: Domain Decomposition Algorithm Implementations for Resilient Numerical Partial Differential Equation Solvers. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1171553.

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Bambha, Neal K., and Shuvra S. Bhattacharyya. A Joint Power/Performance Optimization Algorithm for Multiprocessor Systems Using a Period Graph Construct. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada456719.

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