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: 2 February 2022

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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 (October 1, 2011): 165–67. http://dx.doi.org/10.15373/2249555x/august2014/47.

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Barbulescu, L., A. E. Howe, L. D. Whitley, and M. Roberts. "Understanding Algorithm Performance on an Oversubscribed Scheduling Application." Journal of Artificial Intelligence Research 27 (December 28, 2006): 577–615. http://dx.doi.org/10.1613/jair.2038.

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The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithm's performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm.
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Kaur, Baljit. "Performance Comparison between LMS and NLMS Algorithm." Indian Journal of Applied Research 1, no. 6 (October 1, 2011): 63–65. http://dx.doi.org/10.15373/2249555x/mar2012/20.

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Priya, C. Geetha, and S. Thilagavathi. "Performance of SISID Algorithm for LTE Channel Models." Journal of Advances in Computer Networks 4, no. 1 (2016): 1–5. http://dx.doi.org/10.18178/jacn.2016.4.1.194.

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Hidayat, Trifenaus Prabu, and Andre Sugioko. "Performance Analyzes of Bee Colony Split-Plot Algorithm." International Journal of Information and Education Technology 5, no. 7 (2015): 549–52. http://dx.doi.org/10.7763/ijiet.2015.v5.566.

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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 aspects.
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Wei, Xian Min. "Routing Lookup Algorithm Performance Analysis and Research." Advanced Materials Research 181-182 (January 2011): 109–12. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.109.

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This paper describes several current routing lookup algorithms, to study and analysize the complexity and operating practical performance of these routing lookup algorithms. The results show that although the binary search algorithm is not greatly improved in the searching performance, but in IPv6 environment, because searching performance of multi-branch Trie tree will decrease greatly, thus the superiority of binary search algorithm will be reflected better.
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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 Differential Evolution Algorithm (JADE), Differential Search Algorithm (DSA) and Backtracking Search Optimization Algorithm (BSA)) and some classical image clustering techniques (i.e., k-means, fcm, som networks) have been used to cluster images and their performances have been compared by using four clustering validation indexes. Experimental test results exposed that evolutionary algorithms give more reliable cluster-centers than classical clustering techniques, but their convergence time is quite long.
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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 (November 27, 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 data mining algorithm for Business domain required comparative analysis of different algorithms based on several input parameters such as accuracy, build time and memory usage.To make analysis and comparative study, implementation of popular algorithm required on the basis of literature survey and frequency of algorithm used in present scenario. The performance of algorithms are enhanced and evaluated after applying boosting on the trees. We selected numerical and nominal types of dataset and apply on algorithms. Comparative analysis is perform on the result obtain by the system. Then we apply the new dataset in order to generate generate prediction outcome.
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N, Krishnamoorthy. "TV Shows Popularity and Performance Prediction Using CNN Algorithm." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 1541–50. http://dx.doi.org/10.5373/jardcs/v12sp7/20202257.

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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 performance over an entire year, listing key circuit performance parameters such as efficiency, loading, losses, cost impact, power factor, three phase imbalance, capacity usage and others, providing detailed operating information for the system, and an overview of the performance of every circuit in the system. A diakoptics tearing method and Graph Trace Analysis based distributed computing technology is utilized to speed up the calculation. A general distributed computing architecture is established and a distributed computing algorithm is described. To the best of the authorâ s knowledge, it is the first time that this detailed performance analysis is researched, developed and tested, using a diakoptics based tearing method and Graph Trace Analysis to split the system so that it can be analyzed with distributed computing technology.
Master of Science
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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 au problème de régulation, la recherche opérationnelle a produit un certain nombre de méthodes permettant de répondre efficacement aux perturbations, d’une part dans le secteur métro et d’autre part dans le secteur ferroviaire lourd. En tirant profit de l’état de l’art et des avancées faites dans les deux secteurs, les travaux présentés dans ce manuscrit cherchent à contribuer à l’adaptation des fonctions de régulation des systèmes CBTC pour l’exploitation de lignes ferroviaires suburbaines. L’approche du problème débute par la construction de l’architecture fonctionnelle d’un module de supervision pour un système CBTC standard. Nous proposons ensuite une méthode de régulation basée sur une stratégie de commande prédictive et sur une optimisation multi-objectif des consignes des trains automatiques. Afin d’être en mesure d’évaluer précisément les performances d’une ligne ferroviaire suburbaine équipée d’un automatisme CBTC, il est nécessaire de s’équiper d’un outil de simulation microscopique adapté. Nous présentons dans ce manuscrit l’outil SNCF nommé SIMONE qui permet une simulation réaliste du point de vue fonctionnel et dynamique d’un système ferroviaire incluant un système CBTC. Les objectifs des travaux de thèse nous ont naturellement conduits à prendre part, avec l’équipe SNCF, à la spécification, à la conception et à l’implémentation de cet outil. Finalement, grâce à l’outil SIMONE, nous avons pu tester la méthode de régulation proposée sur des scénarios impliquant des perturbations. Afin d’évaluer la qualité des solutions, la méthode multi-objectif proposée a été comparée à une méthode de régulation individuelle basée sur une heuristique simple. La méthode de régulation multi-objectif propose de bonnes solutions au problème, dans la majorité des cas plus satisfaisantes que celles proposées par la régulation individuelle, et avec un temps de calcul jugé acceptable. Le manuscrit se termine par des perspectives de recherche intéressantes
In high-density area, the demand for railway transportation is continuously increasing. Operating companies turn to new intelligent signaling and control systems, such as Communication Based Train Control (CBTC) systems previously deployed on underground systems only. CBTC systems operate trains in automatic pilot and lead to increase the line capacity without expensive modification of infrastructures. They can also include a supervision module in charge of adapting train behavior according to operating objectives and to disturbances, increasing line robustness. In the literature of real-time traffic management, various methods have been proposed to supervise and reschedule trains, on the one hand for underground systems, on the other hand for railway systems. Making the most of the state-of-the-art in both fields, the presented work intend to contribute to the design of supervision and rescheduling functions of CBTC systems operating suburban railway systems. Our approach starts by designing a supervision module for a standard CBTC system. Then, we propose a rescheduling method based on a model predictive control approach and a multi-objective optimization of automatic train commands. In order to evaluate the performances of a railway system, it is necessary to use a microscopic simulation tool including a CBTC model. In this thesis, we present the tool developed by SNCF and named SIMONE. It allows realistic simulation of a railway system and a CBTC system, in terms of functional architecture and dynamics. The presented work has been directly involved in the design and implementation of the tool. Eventually, the proposed rescheduling method was tested with the tool SIMONE on disturbed scenarios. The proposed method was compared to a simple heuristic strategy intending to recover delays. The proposed multi-objective method is able to provide good solutions to the rescheduling problem and over-performs the simple strategy in most cases, with an acceptable process time. We conclude with interesting perspectives for future work
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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.
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 development on the concept of local likelihood function (LLF) and local posterior probability for parameter estimation, which lead to efficient adaptive filtering algorithms. We also study the convergence performance of these algorithms and their applications by theoretical analyses. As for applications, another important one is to utilize adaptive filters to obtain recursive hypothesis testing and model order selection methods. It is known that the maximum likelihood estimate (MLE) may lead to large variance or ill-conditioning problems when the number of observations is limited. An effective approach to address these problems is to employ various form of regularization in order to reduce the variance at the expense of slightly increased bias. In general, this can be viewed as adopting the Bayesian estimation, where the regularization can be viewed as providing a certain prior density of the parameters to be estimated. By adopting different prior densities in the LLF, we derive the variable regularized QR decomposition-based recursive least squares (VR-QRRLS) and recursive least M-estimate (VR-QRRLM) algorithms. An improved state-regularized variable forgetting factor QRRLS (SR-VFF-QRRLS) algorithm is also proposed. By approximating the covariance matrix in the RLS, new variable regularized and variable step-size transform domain normalized least mean square (VR-TDNLMS and VSS-TDNLMS) algorithms are proposed. Convergence behaviors of these algorithms are studied to characterize their performance and provide useful guidelines for selecting appropriate parameters in practical applications. Based on the local Bayesian estimation framework for linear model parameters developed previously, the resulting estimate can be utilized for recursive nonstationarity detection. This can be cast under the problem of hypothesis testing, as the hypotheses can be viewed as two competitive models between stationary and nonstationary to be selected. In this dissertation, we develop new regularized and recursive generalized likelihood ratio test (GLRT), Rao’s and Wald tests, which can be implemented recursively in a QRRLS-type adaptive filtering algorithm with low computational complexity. Another issue to be addressed in nonstationarity detection is the selection of various models or model orders. In particular, we derive a recursive method for model order selection from the Bayesian Information Criterion (BIC) based on recursive local estimation. In general, the algorithms proposed in this dissertation have addressed some of the important problems in estimation and detection under the local and recursive Bayesian estimation framework. They are intrinsically connected together and can potentially be utilized for various applications. In this dissertation, their applications to adaptive beamforming, ANC system and speech signal processing, e.g. adaptive frequency estimation and nonstationarity detection, have been studied. For adaptive beamforming, the difficulties in determining the regularization or loading factor have been explored by automatically selecting the regularization parameter. For ANC systems, to combat uncertainties in the secondary path estimation, regularization techniques can be employed. Consequently, a new filtered-x VR-QRRLM (Fx-VR-QRRLM) algorithm is proposed and the theoretical analysis helps to address challenging problems in the design of ANC systems. On the other hand, for ANC systems with online secondary-path modeling, the coupling effect of the ANC controller and the secondary path estimator is thoroughly studied by analyzing the Fx-LMS algorithm. For speech signal processing, new approaches for recursive nonstationarity detection with automatic model order selection are proposed, which provides online time-varying autoregressive (TVAR) parameter estimation and the corresponding stationary intervals with low complexity.
published_or_final_version
Electrical and Electronic Engineering
Doctoral
Doctor of Philosophy
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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 result of the simulations were mostly within expectations, faster algorithms still performed better even under heavy loads and even handled the load better than the competition
I denna rapport har vi utfört tester för att utvärdera hur systembelastning påverkar hastigheten på en samling vanligt förekommande algoritmer. Svårigheterna med att teoretiskt räkna ut dessa resultat är på grund av dess många påverkande faktorer. Detta ledde till användandet av en simulation. Ett testsystem skapades för att köra sorteringsalgoritmerna Mergesort, Quicksort och Radixsort med varierad systembelastning. Denna systembelastning skapades genom att generera cachemissar med hjälp av programmet stress-ng. Dessa simulationer, såväl som cache aktiviteten loggades. Resultatet var inom förväntan, de lättare och snabbare algoritmerna klarade sig fortfarande bättre även under svår belastning, och hanterade den ökade belastningen bättre.
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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 between these measures and both performance and robustness are examined, using a model of a directly connected material handling system as a backdrop. The fundamental causes of the relationships and their applicability in the proposed behavior-based optimization approach are discussed.
Ph. D.
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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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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 addressing the problems of large datasets. It minimizes the costs of I/O and time. A CF tree is generated during its working process and clusters are generated after four phases of the whole BIRCH procedure. A drawback of BIRCH is that it is not very scalable. This thesis is devoted to improve accuracy and efficiency of BIRCH algorithm. A sliding window BIRCH algorithm is implemented on the basis of BIRCH algorithm. At the end of thesis, the accuracy and efficiency of sliding window BIRCH are evaluated. A performance comparison among SW BIRCH, BIRCH and K-means are also presented with Silhouette Coefficient index and Calinski-Harabaz Index. The preliminary results indicate that the SW BIRCH may achieve a better performance than BIRCH in some cases.
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Books on the topic "Algorithm performance"

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

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

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

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Smart, John R. Performance evaluation of the NEXRAD Hail Algorithm applied to Colorado thunderstorms. Boulder, Colo: 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. Edwards, Calif: Dryden Flight Research Center, 1995.

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

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

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

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

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Goessens, Walter. Average case analysis of the performance of a modified next-fit binpacking-algorithm. Antwerpen: Universiteit Antwerpen, 1995.

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Book chapters on the topic "Algorithm performance"

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Goldshtein, Sasha, Dima Zurbalev, and Ido Flatow. "Algorithm Optimization." In Pro .NET Performance, 259–75. Berkeley, CA: 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, 301–15. Berlin, Heidelberg: 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, 93–115. Wiesbaden: 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, 286–300. Berlin, Heidelberg: 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, 142–53. Berlin, Heidelberg: 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, 26–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44688-5_3.

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Rahhou, Adnane, and Mohammed Talbi. "Performance Scoring at University: Algorithm of Student Performance." In Information Systems and Technologies to Support Learning, 44–55. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03577-8_6.

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Roe, Michael, Wei Xu, and Dongping Song. "Evaluating the Multiple Objective Genetic Algorithm." In Optimizing Supply Chain Performance, 177–84. London: 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, 164–76. London: 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, 34–40. Berlin, Heidelberg: 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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Mara, Michael, Morgan McGuire, Benedikt Bitterli, and Wojciech Jarosz. "An efficient denoising algorithm for global illumination." In HPG '17: High-Performance Graphics. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3105762.3105774.

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Kourie, Derrick G., Bruce W. Watson, Tinus Strauss, Loek Cleophas, and Melanie Mauch. "Empirically Assessing Algorithm Performance." In the Southern African Institute for Computer Scientist and Information Technologists Annual Conference 2014. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2664591.2664617.

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Branlard, Aboud, Goodnick, and Saraniti. "Efficient memory management for cellular Monte Carlo algorithm." In Electrical Performance of Electronic Packaging. IEEE, 2004. http://dx.doi.org/10.1109/iwce.2004.1407388.

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Kang, Yeonsik, Derek S. Caveney, and J. K. Hedrick. "Performance Analysis of an IMM-Based Obstacle Detection Algorithm." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59627.

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In this paper, two approaches for obstacle detection and position estimation are presented. One is an algorithm based on M out of N detection logic and the other is an algorithm based on the probabilistic Interacting Multiple Model (IMM) method. The M out of N threshold-based algorithm declares that there is an obstacle present if it gets M validated measurements out of N consecutive measurements. IMM algorithm runs two different models in parallel, each based on a different hypothesis. One model assumes that there is an obstacle present while the other model assumes that there is no obstacle present in the sensor field of view. The performances of the two algorithms are compared based on their false alarm rate and detection speed. At first, Monte Carlo simulations are performed using only the false measurements to determine the thresholds for each method that generate a similar number of false detections. Using these thresholds, the detection speed of each method is compared and it is shown that the IMM-based algorithm is superior to the M out of N logic-based algorithm.
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Jelassi, O., and O. Paul. "Markers-based space decomposition algorithm: a new algorithm for multi-fields packet classification." In 2006 Workshop on High Performance Switching and Routing. IEEE, 2006. http://dx.doi.org/10.1109/hpsr.2006.1709679.

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Weinsberg, Yaron, Shimrit Tzur-David, Danny Dolev, and Tal Anker. "One Algorithm to Match Them All: On a Generic NIPS Pattern Matching Algorithm." In 2007 Workshop on High Performance Switching and Routing. IEEE, 2007. http://dx.doi.org/10.1109/hpsr.2007.4281234.

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Khan and Vasileska. "3d Monte Carlo simulation of FinFET using FMM algorithm." In Electrical Performance of Electronic Packaging. IEEE, 2004. http://dx.doi.org/10.1109/iwce.2004.1407392.

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Jacquin, Erwan, David Bellevre, Stephane Cordier, and Bertrand Alessandrini. "Yacht optimiSation Based On Genetic Algorithm Using Ranse Solver." In High Performance Yacht Design Conference. RINA, 2002. http://dx.doi.org/10.3940/rina.ya.2002.31.

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Cousin, P., and J. Valette. "Automatic Optimization Algorithm for Sail Design." In Innovation in High Performance Sailing Yachts 2010. RINA, 2010. http://dx.doi.org/10.3940/rina.innovsail.2010.09.

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Mattson, Tim, David Bader, Jon Berry, Aydin Buluc, Jack Dongarra, Christos Faloutsos, John Feo, et al. "Standards for graph algorithm primitives." In 2013 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2013. http://dx.doi.org/10.1109/hpec.2013.6670338.

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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), August 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. Fort Belvoir, VA: Defense Technical Information Center, July 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), November 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. Fort Belvoir, VA: Defense Technical Information Center, May 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. Fort Belvoir, VA: Defense Technical Information Center, March 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), September 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. Fort Belvoir, VA: Defense Technical Information Center, May 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), August 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. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada456719.

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