Literatura académica sobre el tema "Algorithems"
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Artículos de revistas sobre el tema "Algorithems"
Tian, Xin Cheng y Xiao Hong Deng. "Trajectory Interpolation in CNC Grinding of Indexable Inserts". Advanced Materials Research 97-101 (marzo de 2010): 2007–10. http://dx.doi.org/10.4028/www.scientific.net/amr.97-101.2007.
Texto completoMorsy, H., M. El-khatib, W. Hussein y M. Mahgoub. "INVESTIGATION OF MODERN CONTROL ALGORITHEMS IN MECHATRONIC SYSTEM". International Conference on Applied Mechanics and Mechanical Engineering 15, n.º 15 (1 de mayo de 2012): 1–20. http://dx.doi.org/10.21608/amme.2012.37057.
Texto completoYe, Jun. "Applying Immune Algorithems to the Calculation of Sound Insulation of Walls". Applied Mechanics and Materials 584-586 (julio de 2014): 1853–57. http://dx.doi.org/10.4028/www.scientific.net/amm.584-586.1853.
Texto completoMurtuza, Syed. "A Concis Presentation of Supiervised Learing Algorithems for Feedforward Neural Netwoks". IFAC Proceedings Volumes 27, n.º 9 (agosto de 1994): 91–94. http://dx.doi.org/10.1016/s1474-6670(17)45902-7.
Texto completoLIU, Yanfang. "Application of integration algorithems for elasto-plasticity constitutive model for anisotropic sheet materials". Chinese Journal of Mechanical Engineering (English Edition) 19, n.º 04 (2006): 554. http://dx.doi.org/10.3901/cjme.2006.04.554.
Texto completoDuvvada, Rajeswara Rao, Shaik Ayesha Fathima y Shaik Noorjahan. "A Comprehensive Analysis and Design of Land Cover Usage from Satellite Images using Machine Learning Algorithems". Journal of Visual Language and Computing 2022, n.º 1 (5 de julio de 2022): 25–35. http://dx.doi.org/10.18293/jvlc2022-n1-014.
Texto completoDevi, Kapila y Saroj Ratnoo. "Cluster analysis of socio-economic factors and academic performance of school students". Indonesian Journal of Electrical Engineering and Computer Science 31, n.º 3 (1 de septiembre de 2023): 1568. http://dx.doi.org/10.11591/ijeecs.v31.i3.pp1568-1577.
Texto completoGangavane, Ms H. N. "A Comparison of ABK-Means Algorithm with Traditional Algorithms". International Journal of Trend in Scientific Research and Development Volume-1, Issue-4 (30 de junio de 2017): 614–21. http://dx.doi.org/10.31142/ijtsrd2197.
Texto completoGościniak, Ireneusz y Krzysztof Gdawiec. "Visual Analysis of Dynamics Behaviour of an Iterative Method Depending on Selected Parameters and Modifications". Entropy 22, n.º 7 (2 de julio de 2020): 734. http://dx.doi.org/10.3390/e22070734.
Texto completoSun, Yuqin, Songlei Wang, Dongmei Huang, Yuan Sun, Anduo Hu y Jinzhong Sun. "A multiple hierarchical clustering ensemble algorithm to recognize clusters arbitrarily shaped". Intelligent Data Analysis 26, n.º 5 (5 de septiembre de 2022): 1211–28. http://dx.doi.org/10.3233/ida-216112.
Texto completoTesis sobre el tema "Algorithems"
Saadane, Sofiane. "Algorithmes stochastiques pour l'apprentissage, l'optimisation et l'approximation du régime stationnaire". Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30203/document.
Texto completoIn this thesis, we are studying severa! stochastic algorithms with different purposes and this is why we will start this manuscript by giving historicals results to define the framework of our work. Then, we will study a bandit algorithm due to the work of Narendra and Shapiro whose objectif was to determine among a choice of severa! sources which one is the most profitable without spending too much times on the wrong orres. Our goal is to understand the weakness of this algorithm in order to propose an optimal procedure for a quantity measuring the performance of a bandit algorithm, the regret. In our results, we will propose an algorithm called NS over-penalized which allows to obtain a minimax regret bound. A second work will be to understand the convergence in law of this process. The particularity of the algorith is that it converges in law toward a non-diffusive process which makes the study more intricate than the standard case. We will use coupling techniques to study this process and propose rates of convergence. The second work of this thesis falls in the scope of optimization of a function using a stochastic algorithm. We will study a stochastic version of the so-called heavy bali method with friction. The particularity of the algorithm is that its dynamics is based on the ali past of the trajectory. The procedure relies on a memory term which dictates the behavior of the procedure by the form it takes. In our framework, two types of memory will investigated : polynomial and exponential. We will start with general convergence results in the non-convex case. In the case of strongly convex functions, we will provide upper-bounds for the rate of convergence. Finally, a convergence in law result is given in the case of exponential memory. The third part is about the McKean-Vlasov equations which were first introduced by Anatoly Vlasov and first studied by Henry McKean in order to mode! the distribution function of plasma. Our objective is to propose a stochastic algorithm to approach the invariant distribution of the McKean Vlasov equation. Methods in the case of diffusion processes (and sorne more general pro cesses) are known but the particularity of McKean Vlasov process is that it is strongly non-linear. Thus, we will have to develop an alternative approach. We will introduce the notion of asymptotic pseudotrajectory in odrer to get an efficient procedure
Corbineau, Marie-Caroline. "Proximal and interior point optimization strategies in image recovery". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC085/document.
Texto completoInverse problems in image processing can be solved by diverse techniques, such as classical variational methods, recent deep learning approaches, or Bayesian strategies. Although relying on different principles, these methods all require efficient optimization algorithms. The proximity operator appears as a crucial tool in many iterative solvers for nonsmooth optimization problems. In this thesis, we illustrate the versatility of proximal algorithms by incorporating them within each one of the aforementioned resolution methods.First, we consider a variational formulation including a set of constraints and a composite objective function. We present PIPA, a novel proximal interior point algorithm for solving the considered optimization problem. This algorithm includes variable metrics for acceleration purposes. We derive convergence guarantees for PIPA and show in numerical experiments that it compares favorably with state-of-the-art algorithms in two challenging image processing applications.In a second part, we investigate a neural network architecture called iRestNet, obtained by unfolding a proximal interior point algorithm over a fixed number of iterations. iRestNet requires the expression of the logarithmic barrier proximity operator and of its first derivatives, which we provide for three useful types of constraints. Then, we derive conditions under which this optimization-inspired architecture is robust to an input perturbation. We conduct several image deblurring experiments, in which iRestNet performs well with respect to a variational approach and to state-of-the-art deep learning methods.The last part of this thesis focuses on a stochastic sampling method for solving inverse problems in a Bayesian setting. We present an accelerated proximal unadjusted Langevin algorithm called PP-ULA. This scheme is incorporated into a hybrid Gibbs sampler used to perform joint deconvolution and segmentation of ultrasound images. PP-ULA employs the majorize-minimize principle to address non log-concave priors. As shown in numerical experiments, PP-ULA leads to a significant time reduction and to very satisfactory deconvolution and segmentation results on both simulated and real ultrasound data
Harris, Steven C. "A genetic algorithm for robust simulation optimization". Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1178645751.
Texto completoAlkindy, Bassam. "Combining approaches for predicting genomic evolution". Thesis, Besançon, 2015. http://www.theses.fr/2015BESA2012/document.
Texto completoIn Bioinformatics, understanding how DNA molecules have evolved over time remains an open and complex problem.Algorithms have been proposed to solve this problem, but they are limited either to the evolution of a given character (forexample, a specific nucleotide), or conversely focus on large nuclear genomes (several billion base pairs ), the latter havingknown multiple recombination events - the problem is NP complete when you consider the set of all possible operationson these sequences, no solution exists at present. In this thesis, we tackle the problem of reconstruction of ancestral DNAsequences by focusing on the nucleotide chains of intermediate size, and have experienced relatively little recombinationover time: chloroplast genomes. We show that at this level the problem of the reconstruction of ancestors can be resolved,even when you consider the set of all complete chloroplast genomes currently available. We focus specifically on the orderand ancestral gene content, as well as the technical problems this raises reconstruction in the case of chloroplasts. Weshow how to obtain a prediction of the coding sequences of a quality such as to allow said reconstruction and how toobtain a phylogenetic tree in agreement with the largest number of genes, on which we can then support our back in time- the latter being finalized. These methods, combining the use of tools already available (the quality of which has beenassessed) in high performance computing, artificial intelligence and bio-statistics were applied to a collection of more than450 chloroplast genomes
Astete, morales Sandra. "Contributions to Convergence Analysis of Noisy Optimization Algorithms". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS327/document.
Texto completoThis thesis exposes contributions to the analysis of algorithms for noisy functions. It exposes convergence rates for linesearch algorithms as well as for random search algorithms. We prove in terms of Simple Regret and Cumulative Regret that a Hessian based algorithm can reach the same results as some optimal algorithms in the literature, when parameters are tuned correctly. On the other hand we analyse the convergence order of Evolution Strategies when solving noisy functions. We deduce log-log convergence. We also give a lower bound for the convergence rate of the Evolution Strategies. We extend the work on revaluation by applying it to a discrete settings. Finally we analyse the performance measure itself and prove that the use of an erroneus performance measure can lead to misleading results on the evaluation of different methods
Glaudin, Lilian. "Stratégies multicouche, avec mémoire, et à métrique variable en méthodes de point fixe pour l'éclatement d'opérateurs monotones et l'optimisation". Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS119.
Texto completoSeveral apparently unrelated strategies coexist to implement algorithms for solving monotone inclusions in Hilbert spaces. We propose a synthetic framework for fixed point construction which makes it possible to capture various algorithmic approaches, clarify and generalize their asymptotic behavior, and design new iterative schemes for nonlinear analysis and convex optimization. Our methodology, which is anchored on an averaged quasinonexpansive operator composition model, allows us to advance the theory of fixed point algorithms on several fronts, and to impact their application fields. Numerical examples are provided in the context of image restoration, where we propose a new viewpoint on the formulation of variational problems
Fontaine, Allyx. "Analyses et preuves formelles d'algorithmes distribués probabilistes". Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0091/document.
Texto completoProbabilistic algorithms are simple to formulate. However, theiranalysis can become very complex, especially in the field of distributedcomputing. We present algorithms - optimal in terms of bit complexityand solving the problems of MIS and maximal matching in rings - that followthe same scheme.We develop a method that unifies the bit complexitylower bound results to solve MIS, maximal matching and coloration problems.The complexity of these analyses, which can easily lead to errors,together with the existence of many models depending on implicit assumptionsmotivated us to formally model the probabilistic distributed algorithmscorresponding to our model (message passing, anonymous andsynchronous). Our aim is to formally prove the properties related to theiranalysis. For this purpose, we develop a library, called RDA, based on theCoq proof assistant
Dementiev, Roman. "Algorithm engineering for large data sets hardware, software, algorithms". Saarbrücken VDM, Müller, 2006. http://d-nb.info/986494429/04.
Texto completoDementiev, Roman. "Algorithm engineering for large data sets : hardware, software, algorithms /". Saarbrücken : VDM-Verl. Dr. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=3029033&prov=M&dok_var=1&dok_ext=htm.
Texto completoKhungurn, Pramook. "Shirayanagi-Sweedler algebraic algorithm stabilization and polynomial GCD algorithms". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41662.
Texto completoIncludes bibliographical references (p. 71-72).
Shirayanagi and Sweedler [12] proved that a large class of algorithms on the reals can be modified slightly so that they also work correctly on floating-point numbers. Their main theorem states that, for each input, there exists a precision, called the minimum converging precision (MCP), at and beyond which the modified "stabilized" algorithm follows the same sequence of steps as the original "exact" algorithm. In this thesis, we study the MCP of two algorithms for finding the greatest common divisor of two univariate polynomials with real coefficients: the Euclidean algorithm, and an algorithm based on QR-factorization. We show that, if the coefficients of the input polynomials are allowed to be any computable numbers, then the MCPs of the two algorithms are not computable, implying that there are no "simple" bounding functions for the MCP of all pairs of real polynomials. For the Euclidean algorithm, we derive upper bounds on the MCP for pairs of polynomials whose coefficients are members of Z, 0, Z[6], and Q[6] where ( is a real algebraic integer. The bounds are quadratic in the degrees of the input polynomials or worse. For the QR-factorization algorithm, we derive a bound on the minimal precision at and beyond which the stabilized algorithm gives a polynomial with the same degree as that of the exact GCD, and another bound on the the minimal precision at and beyond which the algorithm gives a polynomial with the same support as that of the exact GCD. The bounds are linear in (1) the degree of the polynomial and (2) the sum of the logarithm of diagonal entries of matrix R in the QR factorization of the Sylvester matrix of the input polynomials.
by Pramook Khungurn.
M.Eng.
Libros sobre el tema "Algorithems"
Smith, Jeffrey Dean. Design and analysis of algorithms. Boston: PWS-KENT Pub. Co., 1989.
Buscar texto completoThe advent of the algorithm: The 300 year journey from an idea to the computer. San Diego, Calif: Harcourt, 2001.
Buscar texto completoBerlinski, David. The advent of the algorithm: The idea that rules the world. New York: Harcourt, 2000.
Buscar texto completoMüller-Hannemann, Matthias y Stefan Schirra. Algorithm engineering: Bridging the gap between algorithm theory and practice. Berlin: Springer, 2010.
Buscar texto completoBaase, Sara. Computer algorithms: Introduction to design and analysis. 2a ed. Reading, Mass: Addison-Wesley Pub. Co., 1991.
Buscar texto completoBaase, Sara. Computer algorithms: Introduction to design and analysis. 2a ed. Reading, Mass: Addison-Wesley Pub. Co., 1988.
Buscar texto completoVerfasserIn, Van Gelder Allen, ed. Computer algorithms: Introduction to design and analysis. 3a ed. Delhi: Pearson Education, 2009.
Buscar texto completoAlgorithm engineering for integral and dynamic problems. Amsterdam: Gordon & Breach, 2001.
Buscar texto completoLance, Chambers, ed. The practical handbook of genetic algorithms: Applications. 2a ed. Boca Raton, Fla: Chapman & Hall/CRC, 2001.
Buscar texto completoH, Jamieson Leah, Gannon Dennis B. 1947- y Douglass Robert J, eds. The characteristics of parallel algorithms. Cambridge, Mass: MIT Press, 1987.
Buscar texto completoCapítulos de libros sobre el tema "Algorithems"
Bez, Helmut y Tony Croft. "Quantum algorithms 2: Simon's algorithm". En Quantum Computation, 333–42. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003264569-23.
Texto completoHendrix, Eligius M. T. y Ana Maria A. C. Rocha. "On Local Convergence of Stochastic Global Optimization Algorithms". En Computational Science and Its Applications – ICCSA 2021, 456–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86976-2_31.
Texto completoBansal, Jagdish Chand, Prathu Bajpai, Anjali Rawat y Atulya K. Nagar. "Conclusion and Further Research Directions". En Sine Cosine Algorithm for Optimization, 105–6. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9722-8_6.
Texto completoLudes-Adamy, Peter y Marcus Schütte. "Immer der Reihe nach – Algorithmen in mathematisch-informatischen Lernumgebungen für den Primarbereich". En Informatisch-algorithmische Grundbildung im Mathematikunterricht der Primarstufe, 3–21. WTM-Verlag Münster, 2022. http://dx.doi.org/10.37626/ga9783959872126.0.01.
Texto completoDas, Sahana, Kaushik Roy y Chanchal Kumar Saha. "A Linear Time Series Analysis of Fetal Heart Rate to Detect the Variability". En Handbook of Research on Recent Developments in Intelligent Communication Application, 471–95. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1785-6.ch018.
Texto completoManoj, Suvvala y Rajendran T. "Higher Prediction Accuracy on Parkinson Disease Patients Using Random Forest Algorithm over DTA". En Advances in Parallel Computing Algorithms, Tools and Paradigms. IOS Press, 2022. http://dx.doi.org/10.3233/apc220081.
Texto completoBouarara, Hadj Ahmed. "A Survey of Computational Intelligence Algorithms and Their Applications". En Handbook of Research on Soft Computing and Nature-Inspired Algorithms, 133–76. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2128-0.ch005.
Texto completoBouarara, Hadj Ahmed. "A Survey of Computational Intelligence Algorithms and Their Applications". En Robotic Systems, 1886–929. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1754-3.ch090.
Texto completoRoy, Provas Kumar. "New Efficient Evolutionary Algorithm Applied to Optimal Reactive Power Dispatch". En Advances in Systems Analysis, Software Engineering, and High Performance Computing, 321–39. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6252-0.ch016.
Texto completoYoucef, Bouras. "Research Information". En Advanced Deep Learning Applications in Big Data Analytics, 218–72. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-2791-7.ch011.
Texto completoActas de conferencias sobre el tema "Algorithems"
Shoukang, Qin. "The Weighted Vector Algorithems in One Person and One Criterion". En The International Symposium on the Analytic Hierarchy Process. Creative Decisions Foundation, 1999. http://dx.doi.org/10.13033/isahp.y1999.077.
Texto completoJia, Haitao y Linjie Luo. "Applying Curriculum Learning on Path-based Knowledge Graph Reasoning Algorithems". En 2021 3rd International Conference on Natural Language Processing (ICNLP). IEEE, 2021. http://dx.doi.org/10.1109/icnlp52887.2021.00019.
Texto completoKanungo, T., M. Y. Jaisimha, J. Palmer y R. M. Haralick. "Methodology for analyzing the performance of detection tasks". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.fcc3.
Texto completoShowalter, Mark, Dennis Hong y Daniel Larimer. "Development and Comparison of Gait Generation Algorithms for Hexapedal Robots Based on Kinematics With Considerations for Workspace". En ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49616.
Texto completoSchmidt, David P. y Christopher J. Rutland. "Reducing Grid Dependency in Droplet Collision Modeling". En ASME 2001 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/2001-ice-395.
Texto completoPerju, Veaceslav y Dorian Saranciuc. "Evaluation of the Multi-Algorithms Targets Recognition Systems". En 12th International Conference on Electronics, Communications and Computing. Technical University of Moldova, 2022. http://dx.doi.org/10.52326/ic-ecco.2022/cs.05.
Texto completoChandrasekaran, Arvind. "Neural Networks". En 8th International Conference on Software Engineering. Academy & Industry Research Collaboration, 2023. http://dx.doi.org/10.5121/csit.2023.131208.
Texto completoDu Pont, Bryony L. y Jonathan Cagan. "An Extended Pattern Search Approach to Wind Farm Layout Optimization". En ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28748.
Texto completoGuan, Yue, Qifan Zhang y Panagiotis Tsiotras. "Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation". En Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/339.
Texto completoGuo, Lei, Lijian Zhou, Shaohui Jia, Li Yi, Haichong Yu y Xiaoming Han. "An Automatic Segmentation Algorithm Used in Pipeline Integrity Alignment Sheet Design". En 2010 8th International Pipeline Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ipc2010-31036.
Texto completoInformes sobre el tema "Algorithems"
Gubaydullina, Zulian, Jan René Judek, Marco Lorenz y Markus Spiwoks. Gestaltungswille und Algorithm Aversion – Die Auswirkungen der Einflussnahme im Prozess der algorithmischen Entscheidungsfindung auf die Algorithm Aversion. Sonderforschungsgruppe Instituionenanalyse, junio de 2021. http://dx.doi.org/10.46850/sofia.9783941627925.
Texto completoJudek, Jan René. Die Bereitschaft zur Nutzung von Algorithmen variiert mit der sozialen Information über die schwache vs. starke Akzeptanz: Eine experimentelle Studie zur Algorithm Aversion. Sonderforschungsgruppe Institutionenanalyse, 2022. http://dx.doi.org/10.46850/sofia.9783947850037.
Texto completoJohansen, Richard A., Christina L. Saltus, Molly K. Reif y Kaytee L. Pokrzywinski. A Review of Empirical Algorithms for the Detection and Quantification of Harmful Algal Blooms Using Satellite-Borne Remote Sensing. U.S. Army Engineer Research and Development Center, junio de 2022. http://dx.doi.org/10.21079/11681/44523.
Texto completoBaader, Franz y Rafael Peñaloza. Axiom Pinpointing in General Tableaux. Aachen University of Technology, 2007. http://dx.doi.org/10.25368/2022.159.
Texto completoBaader, Franz y Rafael Peñaloza. Pinpointing in Terminating Forest Tableaux. Technische Universität Dresden, 2008. http://dx.doi.org/10.25368/2022.166.
Texto completoFiliz, Ibrahim, Jan René Judek, Marco Lorenz y Markus Spiwoks. Die Tragik der Algorithm Aversion. Sonderforschungsgruppe Institutionenanalyse, 2021. http://dx.doi.org/10.46850/sofia.9783941627888.
Texto completoChamplin, Craig y John P. H. Steele. DTPH56-14H-CAP06 Pipeline Assessment through 4-Dimensional Anomaly Detection and Characterization. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), diciembre de 2016. http://dx.doi.org/10.55274/r0011766.
Texto completoBaader, Franz y Rafael Peñaloza. Blocking and Pinpointing in Forest Tableaux. Technische Universität Dresden, 2008. http://dx.doi.org/10.25368/2022.165.
Texto completoLorenz, Markus. Auswirkungen des Decoy-Effekts auf die Algorithm Aversion. Sonderforschungsgruppe Institutionenanalyse, 2022. http://dx.doi.org/10.46850/sofia.9783947850013.
Texto completoBaader, Franz, Jan Hladik y Rafael Peñaloza. PSpace Automata with Blocking for Description Logics. Aachen University of Technology, 2006. http://dx.doi.org/10.25368/2022.157.
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