Literatura científica selecionada sobre o tema "Algorithmes à phases"
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Artigos de revistas sobre o assunto "Algorithmes à phases"
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Domenech, P. "La décision, cette inconnue…". European Psychiatry 30, S2 (novembro de 2015): S51. http://dx.doi.org/10.1016/j.eurpsy.2015.09.145.
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Qu’avons nous appris de l’architecture fonctionnelle des processus de prise de décision dans le cerveau humain grâce aux neurosciences computationnelles ? Dans un premier temps, nous verrons comment les modèles de diffusion ont permis de proposer des algorithmes de décision capable d’expliquer les relations complexes entre proportion de choix et temps de décision observés lors de décision simple, et de faire des prédictions testables sur l’activité cérébrale des régions impliquées dans ces processus cognitifs. En prenant l’exemple de choix économiques simples, nous illustrerons l’intérêt de ce cadre mathématique pour comprendre comment différentes régions cérébrales peuvent interagir pour produire des décisions reflétant nos préférences subjectives. Finalement, nous discuterons autour d’un modèle mathématique capable de détecter les changements d’environnements pour interrompre les tâches en cours et déclencher des phases actives d’exploration afin d’illustrer la façon dont les modèles computationnels permettent de détecter des transitions brutales dans les stratégies comportementales et de prédire avec précision l’activité cérébrale dans le cortex préfrontal humain. Nous conclurons sur l’importance du cadre théorique de l’inférence Bayesienne et, en particulier, des notions de confiance et d’incertitude pour caractériser les algorithmes utilisés par le cerveau humain pour choisir.
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Szekely, D. "La dépression bipolaire : une indication préférentielle de la stimulation cérébrale transcrânienne répétée ?" European Psychiatry 29, S3 (novembro de 2014): 666. http://dx.doi.org/10.1016/j.eurpsy.2014.09.057.
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La prise en charge des patients bipolaires par les stabilisateurs de l’humeur de différentes classes thérapeutiques fait consensus (HAS, 2009). Si les recommandations nationales et internationales fournissent des algorithmes efficients dans le traitement des épisodes aigus maniaques, hypomaniaques et mixtes, la prise en charge des phases dépressives est plus complexe et le clinicien est bien souvent démunis s’il applique « au pied de la lettre » les recommandations. Dans la pratique quotidienne, le recours aux antidépresseurs bien que déconseillé, reste donc largement utilisée par les praticiens, faute de solution alternative efficace à ce jour. Dans cette situation, les recommandations incitent à utiliser les antidépresseurs en association aux stabilisateurs de l’humeur, en cures courtes d’environ 8 à 12 semaines après une réponse thérapeutique satisfaisante, qui ne survient que chez moins de 25 % des patients déprimés bipolaire (HAS, 2009). Le risque de virage de l’humeur induit par les antidépresseurs rapporté dans la littérature est de 3 à 10 % même lorsqu’une association thymorégulatrice est proposée [1].Parmi les alternatives thérapeutiques, la rTMS représente une piste prometteuse : le taux de virage de l’humeur induit est faible (0,84 % d’état maniaque dans le groupe actif vs 0,73 % dans le groupe placebo dans une revue de la littérature publiée par Xia et al. [2], et dans la pratique quotidienne, les déprimés bipolaires semblent répondent plus rapidement que les patients déprimés unipolaires à la rTMS.Nous proposons de faire une revue de la littérature concernant l’efficacité et la tolérance de la rTMS dans cette indication.
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Chin, Marshall H., Nasim Afsar-Manesh, Arlene S. Bierman, Christine Chang, Caleb J. Colón-Rodríguez, Prashila Dullabh, Deborah Guadalupe Duran et al. "Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care". JAMA Network Open 6, n.º 12 (15 de dezembro de 2023): e2345050. http://dx.doi.org/10.1001/jamanetworkopen.2023.45050.
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ImportanceHealth care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income.ObjectiveTo provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity.Evidence ReviewThe Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback.FindingsThe panel developed a conceptual framework to apply guiding principles across an algorithm’s life cycle, centering health and health care equity for patients and communities as the goal, within the wider context of structural racism and discrimination. Multiple stakeholders can mitigate and prevent bias at each phase of the algorithm life cycle, including problem formulation (phase 1); data selection, assessment, and management (phase 2); algorithm development, training, and validation (phase 3); deployment and integration of algorithms in intended settings (phase 4); and algorithm monitoring, maintenance, updating, or deimplementation (phase 5). Five principles should guide these efforts: (1) promote health and health care equity during all phases of the health care algorithm life cycle; (2) ensure health care algorithms and their use are transparent and explainable; (3) authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness; (4) explicitly identify health care algorithmic fairness issues and trade-offs; and (5) establish accountability for equity and fairness in outcomes from health care algorithms.Conclusions and RelevanceMultiple stakeholders must partner to create systems, processes, regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. Reforms should implement guiding principles that support promotion of health and health care equity in all phases of the algorithm life cycle as well as transparency and explainability, authentic community engagement and ethical partnerships, explicit identification of fairness issues and trade-offs, and accountability for equity and fairness.
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Hu, Qijin. "Performance Comparison and Analysis of UCB, ETC, and Thompson Sampling Algorithms in the Multi-Armed Bandit Problem". Highlights in Science, Engineering and Technology 94 (26 de abril de 2024): 273–78. http://dx.doi.org/10.54097/a73zqy52.
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In this study, the nuanced interplay between problem complexity, prior knowledge, and the exploration-exploitation balance is examined, given their critical impact on algorithmic performance in diverse settings. To gain a deeper understanding of these dynamics, three algorithms – Upper Confidence Bound (UCB), Explore-Then-Commit (ETC), and Thompson Sampling – are selected for a comprehensive investigation. Each of these algorithms presents unique approaches to handling the challenges posed by varying problem contexts. The UCB algorithm, known for its robustness in balancing exploration and exploitation, is scrutinized for its performance in environments with differing levels of complexity and uncertainty. This algorithm's reliance on confidence bounds makes it particularly relevant in scenarios where accurate estimates of uncertainty can significantly enhance decision-making processes. ETC, on the other hand, is characterized by its phased approach, initially exploring options before committing to a seemingly optimal choice. This study examines how the ETC algorithm's performance is influenced by the availability of prior knowledge and the intricacy of the problem at hand. Its phased nature makes it a subject of interest in environments where initial exploration can yield substantial insights for subsequent exploitation.
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Amouzou, Gildas Yaovi, e Azzeddine Soulaïmani. "Numerical Algorithms for Elastoplacity: Finite Elements Code Development and Implementation of the Mohr–Coulomb Law". Applied Sciences 11, n.º 10 (19 de maio de 2021): 4637. http://dx.doi.org/10.3390/app11104637.
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Two numerical algorithms for solving elastoplastic problems with the finite element method are presented. The first deals with the implementation of the return mapping algorithm and is based on a fixed-point algorithm. This method rewrites the system of elastoplasticity non-linear equations in a form adapted to the fixed-point method. The second algorithm relates to the computation of the elastoplastic consistent tangent matrix using a simple finite difference scheme. A first validation is performed on a nonlinear bar problem. The results obtained show that both numerical algorithms are very efficient and yield the exact solution. The proposed algorithms are applied to a two-dimensional rockfill dam loaded in plane strain. The elastoplastic tangent matrix is calculated by using the finite difference scheme for Mohr–Coulomb’s constitutive law. The results obtained with the developed algorithms are very close to those obtained via the commercial software PLAXIS. It should be noted that the algorithm’s code, developed under the Matlab environment, offers the possibility of modeling the construction phases (i.e., building layer by layer) by activating the different layers according to the imposed loading. This algorithmic and implementation framework allows to easily integrate other laws of nonlinear behaviors, including the Hardening Soil Model.
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Meshram, Bandu B., Vikas Mendhe e Manish Kumar Singh. "Medical Forensics Principles and Cyber Crime Forensic Investigation Model". Journal of Web Applications and Cyber Security 2, n.º 1 (29 de janeiro de 2024): 1–17. http://dx.doi.org/10.48001/jowacs.2024.211-17.
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The paper deals with medical principles of forensic and their proposed utilization in computer forensic. This paper explores how the medical/traditional forensic science law principles like individuality, exchange, progressive change, comparison analysis, facts do not lie are useful in cybercrime forensic investigation with forensic principles applicability cybercrime scenarios with case law. Lastly the research explores the Digital forensics methodology useful for the prosecution of digital criminals. The researchers have done extensive literature survey of the existing crime investigation forensic investigation frameworks proposed from 1995 to 2022 to identify the detailed activities in each process. Based on this collective information, their limitations and practical experience into the domain, the researchers proposed a robust digital forensic process model to obtain the digital evidence. The authors proposed the digital forensic investigation model with the algorithmic steps used in proposed phases of investigation model. Phase 1 starts the investigation process-readiness phase with procedure 1: digital forensic case management, procedure 2: investigation preparation (fir). Phase 2 seizer and isolation explore for communication shielding. Phase 3: data acquisition/duplication & deleted data recovery explore volatile data collection, non-volatile data, and evidence collection from network with widely used tools with respect to computing OS Infrastructure. The procedures explored in phase 2 are Procedure 3: DataAcquisition (), Procedure 4: Procedure EvidenceCollection () and Procedure 5 HashAlgorithms(). Phase 3 preservation and data security includes packaging, transportation and storage, Access Control and physical Safety. The procedure proposed in Phase3 are Procedure 6: Procedure DataTransfer(). Phase4 Identification, Examination create Procedure7 detailedIdentificationofData(). Phase 4 Digital forensic object Analysis(DFOA) explore analysis of data diagnosis and observe about What, Why, Who When, Where(5W, And How(1H) ? and identify the best deep learning algorithms for examination and analysis for building the investigation tool are identified. The researcher identifies three data bases namely evidence, attacker, and chain of custody for building the report using Procedure 9 Examinationandanalysis() and association of phases with access control, deep learning algorithms and chain of custody. The researcher proposed the design of the secure data structure design of chain of custody and identify the tools used in every phase of the crime investigation.
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McCoy, Airlie J., Ralf W. Grosse-Kunstleve, Paul D. Adams, Martyn D. Winn, Laurent C. Storoni e Randy J. Read. "Phasercrystallographic software". Journal of Applied Crystallography 40, n.º 4 (13 de julho de 2007): 658–74. http://dx.doi.org/10.1107/s0021889807021206.
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Phaseris a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented inPhaserhave been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms have proved to be significantly better than traditional methods in discriminating correct solutions from noise, and for single-wavelength anomalous dispersion experimental phasing, the new algorithms, which account for correlations betweenF+andF−, give better phases (lower mean phase error with respect to the phases given by the refined structure) than those that use meanFand anomalous differences ΔF. One of the design concepts ofPhaserwas that it be capable of a high degree of automation. To this end,Phaser(written in C++) can be called directly from Python, although it can also be called using traditionalCCP4keyword-style input.Phaseris a platform for future development of improved phasing methods and their release, including source code, to the crystallographic community.
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Jeong, Byeong-Min, Yun-Seo Oh, Dae-Sung Jang, Nam-Eung Hwang, Joon-Won Kim e Han-Lim Choi. "Makespan-Minimizing Heterogeneous Task Allocation under Temporal Constraints". Aerospace 10, n.º 12 (14 de dezembro de 2023): 1032. http://dx.doi.org/10.3390/aerospace10121032.
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Task allocation is an essential element for determining the capability of multi-UAV systems to perform various tasks. This paper presents a procedure called a “rebalancing algorithm” for generating task-performing routes in heterogeneous multi-UAV systems. The algorithm adopts a greedy-based heuristic approach to find solutions efficiently in dynamically changing environments. A novel variable named “loitering” is introduced to satisfy temporal constraints, resulting in improved performance compared to heuristic algorithms: a sequential greedy algorithm, a genetic algorithm, and simulated annealing. The rebalancing algorithm is divided into two phases to minimize the makespan, i.e., the initial allocation and reallocation phases. Simulation results demonstrate the proposed algorithm’s effectiveness in highly constrained conditions and its suitability for heterogeneous systems. Additionally, the results show a reduction in calculation time and improved performance compared to the heuristic algorithms.
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Güvenoglu, Büsra, e Belgin Ergenç Bostanoglu. "A qualitative survey on frequent subgraph mining". Open Computer Science 8, n.º 1 (1 de dezembro de 2018): 194–209. http://dx.doi.org/10.1515/comp-2018-0018.
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AbstractData mining is a popular research area that has been studied by many researchers and focuses on finding unforeseen and important information in large databases. One of the popular data structures used to represent large heterogeneous data in the field of data mining is graphs. So, graph mining is one of the most popular subdivisions of data mining. Subgraphs that are more frequently encountered than the user-defined threshold in a database are called frequent subgraphs. Frequent subgraphs in a database can give important information about this database. Using this information, data can be classified, clustered and indexed. The purpose of this survey is to examine frequent subgraph mining algorithms (i) in terms of frequent subgraph discovery process phases such as candidate generation and frequency calculation, (ii) categorize the algorithms according to their general attributes such as input type, dynamicity of graphs, result type, algorithmic approach they are based on, algorithmic design and graph representation as well as (iii) to discuss the performance of algorithms in comparison to each other and the challenges faced by the algorithms recently.
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Ouchitachen, Hicham, Anouar Darif, Mohamed Er-rouidi e Mustapha Johri. "A new optimal strategy for energy minimization in wireless sensor networks". IAES International Journal of Artificial Intelligence (IJ-AI) 13, n.º 2 (1 de junho de 2024): 2265. http://dx.doi.org/10.11591/ijai.v13.i2.pp2265-2274.
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In recent years, evolutionary and metaheuristic algorithms have emerged as crucial tools for optimization in the field of artificial intelligence. These algorithms have the potential to revolutionize various aspects of our lives by leveraging the multidisciplinary nature of wireless sensor networks (WSNs). This study aims to introduce genetic and simulated annealing algorithms as effective solutions for enhancing WSN performance. Our contribution entails two main phases. Firstly, we establish mathematical models and formulate objectives as a nonlinear constrained optimization problem. Secondly, we develop two algorithmic solutions to address the formulated optimization problem. The obtained results from multiple simulations demonstrate the positive impact of the proposed strategies on improving network performance in terms of energy consumption.
Teses / dissertações sobre o assunto "Algorithmes à phases"
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Baala, Oumaya. "Protocole de validation en deux phases : algorithme généralisé". Paris 8, 1996. http://www.theses.fr/1996PA081044.
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La conception des nouvelles applications s'appuie, de plus en plus sur le concept de travail cooperatif caracterise par l'autonomie des sites et l'evolution de la topologie d'execution. Cette classe d'application induit de nouveaux besoins en termes de protocoles de validation atomique tels l'adaptation a toute topologie, l'independance vis-a-vis de tout site particulier et une modularite adequate pour permettre l'evolution de la structure. En partant d'un algorithme asynchrone de detection de terminaison distribuee, nous presentons, d'abord, un algorithme de validation atomique qui s'adapte a tout type de topologie et qui possede un seul initiateur. Nous en deduisons des algorithmes qui s'adaptent sur des topologies classiques telles que l'arbre et l'anneau puis, nous les comparons a d'autres algorithmes de la litterature. Ensuite, nous presentons un algorithme de validation qui peut etre initialise par plusieurs sites a la fois. Enfin, nous analysons les proprietes de ces algorithmes
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Maggiochi, Paul. "Développement d'algorithmes de calcul d'équilibres entre phases pour la simulation des procédés chimiques". Toulouse, INPT, 1986. http://www.theses.fr/1986INPT026G.
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Repertoriation, dans un premier temps, des diverses methodes rencontrees dans la litterature et leurs comparaisons. Puis proposition de la nouvelle methode: quasilineaire en debut de recherches, puis connexion (si necessaire) sur une methode de quasi-newton pour accelerer la convergence. Test sur divers flashes di et tri-phasiques
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Deredempt, Olivier. "Étude comparative des algorithmes de recherche des phases de la porteuse et de l'horloge de bits d'un signal à modulation de phase". Toulouse, INPT, 1993. http://www.theses.fr/1993INPT150H.
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Le but de cette these est d'etudier differentes techniques de recherche des phases de la porteuse et de l'horloge de bits pour un signal a modulation de phase. Dans le premier chapitre, nous appliquons le critere du maximum de vraisemblance dans le cas d'un signal de telecommunications en modulations mdpm. Les deuxieme et troisieme chapitres sont consacres a l'etablissement des expressions des algorithmes obtenus dans le chapitre precedent. Le quatrieme chapitre donne le calcul mathematique des caracteristiques pour un filtre de reception en cosinus sureleve. Enfin, le dernier chapitre montre le resultat des simulations de la chaine de transmission avec differents systemes de synchronisation
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Przybylski, Anthony. "Méthode en deux phases pour la résolution exacte de problèmes d'optimisation combinatoire comportant plusieurs objectifs : nouveaux développements et application au problème d'affectation linéaire". Nantes, 2006. http://www.theses.fr/2006NANT2123.
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Dans ce travail, nous nous intéressons à la résolution exacte de problèmes d'optimisation combinatoire multi-objectif par la méthode en deux phases. Pour cela, nous utilisons le problème d'affectation comme support de nos investigations. La méthode en deux phases est un cadre de résolution général qui a été popularisé par Ulungu en 1993 avec comme idée centrale d'exploiter la structure spécifique des problèmes d'optimisation combinatoire pour leur résolution dans un contexte multi-objectif. Elle a depuis été appliquée sur un grand nombre de problèmes, en se limitant toutefois au contexte bi-objectif. Nous apportons des affinements à cette méthode et à son application au problème d'affectation bi-objectif. En particulier, nous proposons des bornes supérieures améliorées et l'utilisation d'un algorithme de ranking comme principale routine pour la seconde phase de la méthode. Nous proposons ensuite une généralisation de cette méthode au contexte multi-objectif, qui est réalisée en deux temps. Pour la première phase, une analyse de la décomposition de l'ensemble des poids en correspondance avec les points supportés extrêmes, nous permet de mettre en évidence une notion d'adjacence géométrique entre ces points, et une condition d'exhaustivité sur leur énumération. La seconde phase consiste en la définition et l'exploration de régions dans lesquelles des énumérations sont nécessaires afin d'achever la résolution du problème. Notre solution repose essentiellement sur une description appropriée de ces régions qui en permet une exploration par analogie avec le cas bi-objectif, et permet donc la réutilisation de stratégies d'exploration existantes pour ce contexte. Les résultats expérimentaux sur le problème d'affectation tri-objectif attestent de l'efficacité de la méthodeThe purpose of this work is the exact solution of multi-objective combinatorial optimisation problems with the two phase method. For this, we use assignment problem as a support for our investigations. The two phase method is a general solving scheme that has been popularized by Ulungu in 1993. The main idea of this method is to exploit the specific structure of combinatorial optimisation problems in a multi-objective context. It has been applied to a number of problems, with a limitation on the bi-objective case. We present improvements in this method and in its application to the bi-objective assignment problem. In particular, we propose improved upper bounds and the use of a ranking algorithm as main routine in the second phase of the method. We propose next a generalisation of this method to the multi-objective case, done in two steps. For the first phase, we analyse the weight set decomposition in correspondance with the nondominated extreme points. This allows us to highlight a geometric notion of adjacency between these points and an optimality condition on their enumeration. The second phase consists in the definition and the exploration of the area inside of which enumerations are required to finalize the resolution to the problem. Our solution is based primarily on an appropriate description of this area, that allows to explore it by analogy with the bi-objective case. It is therefore possible to reuse a strategy developped for this case. Experimental results on three-objective assignment problem show the efficiency of the method
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Vincent, Thomas. "Caractérisation des solutions efficaces et algorithmes d’énumération exacts pour l’optimisation multiobjectif en variables mixtes binaires". Nantes, 2013. http://archive.bu.univ-nantes.fr/pollux/show.action?id=c984a17c-6904-454d-9b3a-e63846e9fb9b.
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Dans ce travail, nous nous intéressons à la résolution exacte de problèmes d’optimisation multiobjectif en variables mixtes binaires. La nature mixte des variables introduit d’importantes différences par rapport aux contextes purement discrets ou continus. Nous proposons donc de prendre en compte ces différences grâce à une représentation appropriée des ensembles de solutions ainsi qu’une procédure de mise à jour dédiée. Ces propositions nous permettent, dans le contexte biobjectif, d’adapter deux méthodes de résolution usuellement appliquées aux problèmes combinatoires : la procédure de Branch & Bound et la méthode en deux phases. Nous proposons de nombreux affinements pour ces méthodes, comme de nouveaux ensembles bornant ou des stratégies de cheminement. À partir de nos observations sur leurs performances, nous proposons une nouvelle routine pour la seconde phase de la méthode en deux phases, reprenant les points forts des méthodes étudiées. Dans le contexte triobjectif, nous étendons notre représentation des ensembles de solutions en procédant par analogie avec le cas biobjectif. Les méthodes de résolution sont également adaptées à ce contexte et étudiées. En particulier, la décomposition de la zone de recherche lors de la seconde phase est décrite en détail. La solution logicielle proposée a été appliquée sur un problème réel : l’évaluation d’une politique de choix de véhicules. Les choix concernés vont de véhicules conventionnels aux véhicules électriques, eux-mêmes alimentés par une source d’électricité classique ou par panneaux solairesThe purpose of this work is the exact solution of multiple objective binary mixed integer linear programmes. The mixed nature of the variables implies significant differences with purely continuous or purely discrete programmes. Thus, we propose to take these differences into account using a proper representation of the solution sets and a dedicated update procedure. These propositions allow us to adapt for the biobjective case two solution methods commonly used for combinatorial problems: the Branch & Bound algorithm and the two phase method. Several improvements are proposed, such as bound sets or visiting strategies. We introduce a new routine for the second phase of the two phase method that takes advantage of all the relevant features of the previously studied methods. In the 3-objective context, the solution sets representation is extended by analogy with the biobjective case. Solutions methods are extended and studied as well. In particular, the decomposition of the search area during the second phase is thoroughly described. The proposed software solution has been applied on a real world problem: evaluation of a vehicle choice policy. The possible choices range from classical to electric vehicles that are powered by grid or solar power
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Mahamdi, Célia. "Multi-Consensus distribué : agrégation et révocabilité". Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS426.
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Cette thèse présente deux contributions dans le domaine des systèmes distribués : OMAHA et le Consensus f-Révocable. OMAHA (Opportunistic Message Aggregation for pHase-based Algorithms) est un mécanisme d'agrégation de messages conçu pour les algorithmes à phases. Dans les environnements Cloud, où plusieurs applications partagent la même infrastructure, la bande passante est une ressource critique. Dans les datacenters, une partie importante du trafic est consacrée aux petits messages. Chaque message possède un en-tête, ainsi, l'accumulation de ces petits messages pose un véritable problème et entraîne une consommation non négligeable de bande passante. Plusieurs mécanismes ont été proposés pour adresser ce défi, mais peu d'entre eux prennent en compte les caractéristiques applicatives. Ils reposent principalement sur une agrégation des messages au niveau de la couche réseau. OMAHA exploite les spécificités des algorithmes à phases pour agréger intelligemment et de manière opportuniste les messages. Bien que gourmands en messages, de très nombreuses applications reposent sur des algorithmes à phases (Google Spanner, Zookeeper, etc.). Cependant, ils possèdent un avantage majeur : des communications prévisibles. En anticipant les futures communications, OMAHA retarde les messages en les regroupant avec d'autres destinés au même processus. Cela permet de réduire le nombre de messages envoyés sur le réseau et donc une économie de bande passante. Nos expériences montrent des économies de bande passante allant jusqu'à 30%, tout en limitant la dégradation de la latence à 5% pour le célèbre algorithme de Paxos. Dans les systèmes distribués, atteindre un consensus sur une action ou une valeur est un défi complexe, surtout lorsque les processus sont soumis à des contraintes. De nombreux systèmes, tels que les systèmes multi-agents (véhicules autonomes, gestion d'agenda, robotique, etc.) ou encore les systèmes d'allocation de ressources, doivent respecter des contraintes tout en atteignant un objectif global commun. Cependant, les algorithmes de consensus traditionnels ne prennent pas en compte ces contraintes, la décision se basant uniquement sur les valeurs proposées par les processus. Une solution triviale consisterait à recueillir toutes les contraintes, mais en raison de l'asynchronisme et des pannes, cela est impossible. Pour tolérer les pannes, certains algorithmes définissent un nombre maximal de fautes qu'ils peuvent supporter. Cela permet à l'algorithme de progresser sans attendre la réponse de tous les processus. En conséquence, la valeur décidée est souvent imposée par un sous-ensemble de processus, la majorité. Les contraintes de la minorité sont ainsi ignorées. Pour répondre à ce problème, nous avons introduit le Consensus f-Révocable. Ce consensus revisité permet de choisir une valeur qui respecte les contraintes des processus tout en offrant la possibilité de révoquer une décision prise par la majorité si celle-ci viole les contraintes d'un processus de la minorité. La convergence est assurée car le nombre de révocations est borné par le nombre de processus appartenant à la minorité. Nous avons développé deux adaptations de l'algorithme Paxos pour mettre en pratique ce nouveau consensusThis thesis presents two contributions to the field of distributed systems: OMAHA and the f-Revoke Consensus.OMAHA (Opportunistic Message Aggregation for pHase-based Algorithms) is a message aggregation mechanism designed for phase-based algorithms. In cloud environments, multiple applications share the same infrastructure, making bandwidth a critical resource. A significant portion of traffic in data centers consists of small messages. Each message includes a header, leading to substantial bandwidth consumption. Several mechanisms have been proposed to address this issue, but few consider application-specific characteristics. Most rely on aggregation at the network layer. OMAHA leverages the features of phase-based algorithms to intelligently and opportunistically aggregate messages. Many applications, such as Google Spanner and Zookeeper, depend on phase-based algorithms. They are often message-intensive but offer a key advantage: predictable communications. By anticipating future communications, OMAHA delays messages and groups them with others intended for the same process. This approach reduces the number of messages sent over the network, resulting in bandwidth savings. Our experiments show bandwidth saving of up to 30%, while limiting latency degradation to 5% for the well-known Paxos algorithm. In distributed systems, achieving consensus on an action or value is complex, especially when processes face constraints. Many systems, including multi-agent systems (like autonomous vehicles and robotics) and resource allocation systems, need to respect these constraints while working towards a common goal. Unfortunately, traditional consensus algorithms often overlook these constraints, focusing only on the values proposed by the processes. A straightforward solution would be to gather all constraints, but due to asynchrony and potential failures, this is impossible. To handle failures, some algorithms set a limit on the number of faults they can tolerate. This allows them to move forward without waiting for responses from every process. As a result, the final decision is made by a subset of processes known as the majority. This leads to the exclusion of constraints from the minority. To tackle this problem, we introduced the f-Revoke Consensus. This new approach enables the selection of a value that considers processes' constraints. It also allows for the revocation of a majority decision if it violates the constraints of a minority process. Importantly, convergence is ensured because the number of revocations is limited by the size of the minority. We developed two adaptations of the Paxos algorithm to implement this new consensus
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Hollette, Matthieu. "Modélisation de la propagation des ondes élastiques dans un milieu composite à microstructure 3D". Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00840603.
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En contrôle non-destructif par ultrasons, la simulation présente un intérêt majeur en permettant à la fois d'optimiser les configurations de contrôle des pièces et de simplifier l'analyse des données acquises. Cette thèse traite de la modélisation de la propagation des ultrasons dans les matériaux composites tissés. Ces matériaux sont constitués de fibres de Carbone (micrométriques) regroupées en mèches (millimétriques) qui sont ensuite tissées pour former une couche de matériau : leur structure est donc hétérogène à deux échelles distinctes. L'étude à l'échelle du tissage nécessite la connaissance préalable des propriétés mécaniques des mèches. Nous proposons deux méthodes visant à effectuer l'homogénéisation dynamique du matériau à l'échelle microscopique. Une première consiste à identifier les rigidités complexes d'un milieu effectif représentatif de la mèche en comparant les nombres d'ondes des modes guidés s'y propageant à ceux calculés dans un milieu hétérogène de même géométrie ; nous avons développé un algorithme génétique permettant de faire correspondre les jeux de nombres d'onde, dont l'application permet d'identifier certaine des rigidités recherchées. La seconde consiste à étendre un modèle existant permettant d'homogénéiser la structure de la mèche en tenant compte de la diffraction multiple des ondes de volume par les fibres. Le modèle initial (modèle à trois phases) ne traitant que le cas de l'incidence normale aux fibres est étendu au cas plus complexe de l'incidence oblique : un calcul de la diffraction multiple en incidence oblique par un réseau dense de fibres et tenant compte de l'anisotropie des différents milieux est donc proposé. Comme pour la première méthode, on utilise un algorithme génétique pour effectuer l'identification des rigidités effectives. Les résultats obtenus nous amènent à remettre en cause certaines hypothèses de base faites pour effectuer cette homogénéisation dynamique ; particulièrement, la dépendance des résultats à l'angle d'incidence semble remettre en cause le choix de la loi de Hooke comme loi fondamentale pour effectuer une homogénéisation dynamique des composites à structures complexes.
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Deroulers, Christophe. "Application de la mécanique statistique à trois problèmes hors d'équilibre : algorithmes, épidémies, milieux granulaires". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2006. http://tel.archives-ouvertes.fr/tel-00102083.
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Cette thèse de doctorat étudie trois problèmes à l'aide des outils de la mécanique statistique. Nous montrons l'existence du phénomène d'universalité critique pour la transition de phases dynamique de certains algorithmes de recherche combinatoire. Nous donnons les valeurs exactes des exposants critiques et une formule analytique pour une fonction d'échelle. Nous développons un formalisme qui nous permet de calculer un développement perturbatif systématique, en grandes dimensions d'espace, de la fonction de grandes déviations de l'état métastable du processus de contact. Il peut resservir entre autres pour d'autres modèles de biologie des populations. Nous introduisons enfin deux modèles bidimensionnels exactement solubles pour la statique des milieux granulaires. Ils reproduisent la transition de jamming et permettent de discuter les différentes échelles de longueurs de ces milieux et de mettre en défaut l'hypothèse d'Edwards dans un cas réaliste.
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Ben, Sedrine Emna. "Machines à commutation de flux à grand nombre de phases : modèles comportementaux en mode dégradé et élaboration d’une stratégie de commande en vue de l’amélioration de la tolérance aux pannes". Thesis, Cachan, Ecole normale supérieure, 2014. http://www.theses.fr/2014DENS0047/document.
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Dans cette thèse, nous nous sommes intéressés à l'étude des modèles comportementaux en mode dégradé des machines pentaphasées à commutation de flux (MCF pentaphasée). Tout d'abord, une comparaison des performances électromagnétiques de cette machine à une machine triphasée équivalente est tout d'abord effectuée. Ces performances sont calculées par la méthode des Eléments Finis (EF 2D) et validées expérimentalement. Les résultats ont montré l'apport de la machine pentaphasée avec un couple massique plus élevé, une ondulation de couple plus faible, un courant de court-circuit plus faible et sa capacité à tolérer des défauts de phases. L'étude de la tolérance aux ouvertures de phases est alors élaborée pour cette MCF pentaphasée. Le comportement de la machine en cas d'ouvertures de phases (du point de vue du couple moyen, de l'ondulation de couple, des pertes Joule et du courant dans le neutre) est présenté. Ensuite, des méthodes de reconfiguration en vue d'améliorer le fonctionnement sont proposées dont une reconfiguration minimale permettant de se retrouver avec une alimentation équivalente à celle d'une machine tétraphasée ou triphasée, un calcul analytique des courants optimaux permettant d'annuler à la fois le courant du neutre et l'ondulation du couple tout en assurant le couple moyen, et finalement une reconfiguration assurée par un algorithme génétique d'optimisation qui est un algorithme non-déterministe multi-objectifs et multi-contraintes. Diverses combinaisons des différents objectifs et contraintes sont, dans ce cadre, effectuées et les courants optimaux sont injectés dans le modèle EF 2D de la machine pour vérifier si les performances ont été améliorées. Le modèle analytique du couple pris en compte dans l'algorithme d'optimisation est alors révisé pour prendre en compte l'influence du mode dégradé. Les différentes solutions du front de Pareto sont analysées et les performances électromagnétiques sont bien améliorées. Cela est vérifié par les calculs EF 2D et suivi d'une validation expérimentale. L'influence des défauts sur les forces magnétiques radiales est également analysée. Dans une seconde partie, l'étude de la tolérance de la machine pentaphasée à commutation de flux aux défauts de courts-circuits est effectuée. Les premières étapes d'isolation des défauts de courts-circuits sont proposées. Par la suite, les courants de courts-circuits, prenant en compte l'effet reluctant de la machine, sont calculés analytiquement et leurs effets sur les performances de la machine sont analysés. Les reconfigurations sont aussi calculées par l'algorithme génétique d'optimisation et les nouvelles références des courants permettent d'améliorer le fonctionnement en mode dégradé. Tous les résultats sont validés par la méthode des EF 2D et expérimentalement. En conclusion, des comparaisons entre la tolérance aux défauts d'ouvertures et de courts-circuits de la machine pentaphasée à commutation de flux sont effectuées et ont permis de conclure quant au fonctionnement de cette machine en modes sain et dégradé avec et sans correction. Les résultats analytiques, numériques et expérimentaux ont montré la bonne efficacité de la commande proposée pour l'amélioration de la tolérance aux défauts d'ouvertures et courts-circuits de phasesIn this thesis, we are interested in the study of a five-phase flux switching permanent magnet machine (five-phase FSPM machine) behavior in healthy and faulty mode. First, a comparison of electromagnetic performances between this machine and an equivalent three-phase machine is carried out. These performances are calculated by a Finite Element (FE 2D) model and validated by experiments. Results showed the five-phase machine contribution with a higher torque density, lower torque ripples, lower short-circuit current and ability to tolerate phases faults. The study of open-circuit tolerance is then developed for this five-phase FSPM. The behavior of the machine (the average torque, torque ripples, copper losses and the current in the neutral) in the case of open-circuit on a single and two adjacent and non-adjacent phases is presented. Then reconfiguration methods to improve the operation are proposed including a minimum reconfiguration allowing to end up with a feeding equivalent to that of a three-phase or a four-phase machine, an analytical calculation of optimal currents to cancel both the neutral current and torque ripples while ensuring the average torque, and finally a reconfiguration performed by a genetic optimization algorithm which is a non-deterministic algorithm multi-objective functions and multi-constraints. In this context, various combinations of different objectives and constraints are proposed and optimal currents are injected into the 2D FE model of the machine to see if performances have been improved. The analytical model of the torque used in the optimization algorithm is then revised to take into account the influence of the degraded mode. Different solutions of Pareto front are analyzed and electromagnetic performances are improved. This is verified by FE 2D calculations and followed by experimental validation. Faults impact on the radial magnetic forces is also analyzed. In the second part of this work, the study of the five-phase FSPM machine tolerance to short-circuit faults is performed. First steps of the faults isolation are proposed. Thereafter, short-circuit currents, taking into account the reluctance machine impact, are calculated analytically and their effects on machine performances are analyzed. Reconfigurations are also calculated by the genetic algorithm optimization and new references currents improved the degraded mode operation. All results are validated by the FE 2D calculation and experimentally. In conclusion, comparisons between fault-tolerance to phases openings and short-circuits of the five-phase FSPM machine are performed. Results led to conclude regarding the operation of this machine in healthy and degraded modes with and without correction. Analytical, numerical and experimental results showed good efficiency of the proposed control to improve fault-tolerance to phases openings and short-circuits
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Lesieur, Thibault. "Factorisation matricielle et tensorielle par une approche issue de la physique statistique". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS345/document.
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Dans cette thèse, je présente des résultats sur la factorisation de matrice et de tenseur. Les matrices étant un objet omniprésent en mathématique, un grand nombre de problèmes d'apprentissage machine peuvent être transcrits en un problème de factorisation de matrice de petit rang. C'est une des méthodes les plus basiques utilisée dans les méthodes d'apprentissage non supervisé et les problèmes de réduction dimensionnelle. Les résultats présentés dans cette thèse ont pour la plupart déjà été inclus dans des publications antérieures [LKZ 2015]. Le problème de la factorisation de matrice de petit rang devient de plus en plus difficile quand on rajoute des contraintes additionnelles, comme par exemple la positivité d'un des facteurs. Nous présentons ici un cadre dans lequel analyser ce problème sous un angle Bayésien où les priors sur les facteurs peuvent être génériques et où l'output channel à travers duquel la matrice est observée peut être générique aussi. Nous tracerons un parallèle entre le problème de factorisation matricielle et les problèmes de verre de spin vectoriel. Ce cadre permet d'aborder d'une façon unifiée des problèmes qui étaient abordés de façon séparée dans des publications précédentes. Nous dérivons en détail la forme générale des équations de Low-rank Approximate Message Passing (Low-RAMP) ce qui donnera un algorithme de factorisation. Ces équations sont connues en physique statistique sous le nom des équations TAP. Nous dérivons ces équations dans différents cas, pour le modèle de Sherrington-Kirkpatrick, les restricted Boltzmann machine, le modèle de Hopfield ou encore le modèle xy. La dynamique des équations Low-RAMP peut être analysée en utilisant les équations de State Evolution; ces équations sont équivalentes à un calcul des répliques symétriques. Dans la section dévolue aux résultats nous étudierons de nombreux diagrammes de phase et transition de phase dans le cas Bayes-optimale. Nous présenterons différentes typologies de diagrammes de phase et leurs interprétations en terme de performances algorithmiquesIn this thesis we present the result on low rank matrix and tensor factorization. Matrices being such an ubiquitous mathematical object a lot of machine learning can be mapped to a low-rank matrix factorization problem. It is for example one of the basic methods used in data analysis for unsupervised learning of relevant features and other types of dimensionality reduction. The result presented in this thesis have been included in previous work [LKZ 201].The problem of low rank matrix becomes harder once one adds constraint to the problem like for instance the positivity of one of the factor of the factorization. We present a framework to study the constrained low-rank matrix estimation for a general prior on the factors, and a general output channel through which the matrix is observed. We draw a paralel with the study of vector-spin glass models -- presenting a unifying way to study a number of problems considered previously in separate statistical physics works. We present a number of applications for the problem in data analysis. We derive in detail ageneral form of the low-rank approximate message passing (Low-RAMP) algorithm that is known in statistical physics as the TAP equations. We thus unify the derivation of the TAP equations for models as different as the Sherrington-Kirkpatrick model, the restricted Boltzmann machine, the Hopfield model or vector (xy, Heisenberg and other) spin glasses. The state evolution of the Low-RAMP algorithm is also derived, and is equivalent to the replica symmetric solution for the large class of vector-spin glass models. In the section devoted to result we study in detail phase diagrams and phase transitions for the Bayes-optimal inference in low-rank matrix estimation. We present a typology of phase transitions and their relation to performance of algorithms such as the Low-RAMP or commonly used spectral methods
Livros sobre o assunto "Algorithmes à phases"
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Engle, Stanley E. Roundoff algorithms for digital phase shifters that minimize beam shift. Monterey, Calif: Naval Postgraduate School, 1992.
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D, Pritt Mark, ed. Two-dimensional phase unwrapping: Theory, algorithms, and software. New York: Wiley, 1998.
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Peter, McMenamin. Development of MD-DRG algorithms: Phase I final report. Springfield, Va: Mandex, Inc., 1986.
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Smith, Jeffrey V. A new stoichiometric algorithm for computing phase equilibrium. Ottawa: National Library of Canada, 1990.
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Lin, Shu. On decoding of multi-level MPSK modulation codes. Honululu, Hawaii: Dept. of Electrical Engineering, University of Hawaii at Manoa, 1990.
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University of Hawaii at Manoa. Dept. of Electrical Engineering. e Goddard Space Flight Center, eds. On decoding of multi-level MPSK modulation codes. Honululu, Hawaii: Dept. of Electrical Engineering, University of Hawaii at Manoa, 1990.
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Shu, Lin. On decoding of multi-level MPSK modulation codes. Honululu, Hawaii: Dept. of Electrical Engineering, University of Hawaii at Manoa, 1990.
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Jonathan, Frank, Beerman Henry e United States. National Aeronautics and Space Administration., eds. Multicolor pyrometer for materials processing in space, phase II. [Washington, DC: National Aeronautics and Space Administration, 1988.
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Jonathan, Frank, Beerman Henry e United States. National Aeronautics and Space Administration., eds. Multicolor pyrometer for materials processing in space, phase II. [Washington, DC: National Aeronautics and Space Administration, 1989.
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Ambrose, Dean H. Three-dimensional graphics simulator for testing mine machine computer-controlled algorithms: Phase 1, development. Washington, D.C: U.S. Dept. of the Interior, Bureau of Mines, 1992.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Algorithmes à phases"
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Brazdil, Pavel, Jan N. van Rijn, Carlos Soares e Joaquin Vanschoren. "Metalearning Approaches for Algorithm Selection I (Exploiting Rankings)". In Metalearning, 19–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-67024-5_2.
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SummaryThis chapter discusses an approach to the problem of algorithm selection, which exploits the performance metadata of algorithms (workflows) on prior tasks to generate recommendations for a given target dataset. The recommendations are in the form of rankings of candidate algorithms. The methodology involves two phases. In the first one, rankings of algorithms/workflows are elaborated on the basis of historical performance data on different datasets. These are subsequently aggregated into a single ranking (e.g. average ranking). In the second phase, the average ranking is used to schedule tests on the target dataset with the objective of identifying the best performing algorithm. This approach requires that an appropriate evaluation measure, such as accuracy, is set beforehand. In this chapter we also describe a method that builds this ranking based on a combination of accuracy and runtime, yielding good anytime performance. While this approach is rather simple, it can still provide good recommendations to the user. Although the examples in this chapter are from the classification domain, this approach can be applied to other tasks besides algorithm selection, namely hyperparameter optimization (HPO), as well as the combined algorithm selection and hyperparameter optimization (CASH) problem. As this approach works with discrete data, continuous hyperparameters need to be discretized first.
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Hendrix, Eligius M. T., e Ana Maria A. C. Rocha. "On Local Convergence of Stochastic Global Optimization Algorithms". In 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.
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AbstractIn engineering optimization with continuous variables, the use of Stochastic Global Optimization (SGO) algorithms is popular due to the easy availability of codes. All algorithms have a global and local search character, where the global behaviour tries to avoid getting trapped in local optima and the local behaviour intends to reach the lowest objective function values. As the algorithm parameter set includes a final convergence criterion, the algorithm might be running for a while around a reached minimum point. Our question deals with the local search behaviour after the algorithm reached the final stage. How fast do practical SGO algorithms actually converge to the minimum point? To investigate this question, we run implementations of well known SGO algorithms in a final local phase stage.
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Høyer, Peter. "The Phase Matrix". In Algorithms and Computation, 308–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11602613_32.
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Korolyuk, Vladimir S., e Vladimir V. Korolyuk. "Phase merging algorithms". In Stochastic Models of Systems, 43–87. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4625-8_3.
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Guan, Ji, Wang Fang e Mingsheng Ying. "Robustness Verification of Quantum Classifiers". In Computer Aided Verification, 151–74. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_7.
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AbstractSeveral important models of machine learning algorithms have been successfully generalized to the quantum world, with potential speedup to training classical classifiers and applications to data analytics in quantum physics that can be implemented on the near future quantum computers. However, quantum noise is a major obstacle to the practical implementation of quantum machine learning. In this work, we define a formal framework for the robustness verification and analysis of quantum machine learning algorithms against noises. A robust bound is derived and an algorithm is developed to check whether or not a quantum machine learning algorithm is robust with respect to quantum training data. In particular, this algorithm can find adversarial examples during checking. Our approach is implemented on Google’s TensorFlow Quantum and can verify the robustness of quantum machine learning algorithms with respect to a small disturbance of noises, derived from the surrounding environment. The effectiveness of our robust bound and algorithm is confirmed by the experimental results, including quantum bits classification as the “Hello World” example, quantum phase recognition and cluster excitation detection from real world intractable physical problems, and the classification of MNIST from the classical world.
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Parker, Thomas S., e Leon O. Chua. "Phase Portraits". In Practical Numerical Algorithms for Chaotic Systems, 269–300. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3486-9_10.
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Dupain, Yves, Michel Mendes France e Claud Tricot. "Spirals and Phase Transitions". In Algorithms, Fractals, and Dynamics, 59–62. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4613-0321-3_4.
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Kurgalin, Sergei, e Sergei Borzunov. "Phase Evaluation Algorithm". In Texts in Computer Science, 53–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65052-0_9.
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Hurt, Norman E. "Reconstruction Algorithms in Two Dimensions". In Phase Retrieval and Zero Crossings, 151–64. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-010-9608-9_11.
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Stomp, F. A., e W. P. de Roever. "Designing distributed algorithms by means of formal sequentially phased reasoning". In Distributed Algorithms, 242–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/3-540-51687-5_47.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Algorithmes à phases"
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Kwaśny, A., M. Krakowski e G. Soboń. "Optimization of femtosecond pulses by AI-assisted spectral phase modulation: influence of spectral resolution". In CLEO: Applications and Technology, JW2A.49. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_at.2024.jw2a.49.
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We investigate the possibility of optimization of ultrashort laser pulses by spectral phase modulation using machine learning algorithms. The Grey Wolf Algorithm is applied, and the efficiency of various spectral resolution patterns is examined.
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Garnaoui, H., e A. H. Tewfik. "Multigrid phase retrieval". In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.thy26.
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The problem of reconstructing an object function from the modulus of its Fourier transform arises in many disciplines. Several algorithms have been proposed to solve this problem. One of the most successful of those algorithms is the iterative transform algorithm, but is has a disadvantage in that it stagnates before it reaches a solution in some cases. Here, we propose a multigrid adaptation of this algorithm to speed up convergence. We also propose a second algorithm that attempts to solve the problem entirely in the space domain by using the support constraint and the nonlinear correlation equations. This algorithm is based on an iterative global linearization of the correlation equations. For both algorithms, several cycles of the basic iterative procedure are performed until stagnation is detected or until the number of cycles reaches a predetermined upper limit. At this point, the error and the current object-function estimate are transferred to a coarser grid, and the same basic iterative algorithm is then used to compute a grid correction to the last estimate that was computed on the fine grid. We show that a multigrid generalization of this two-grid procedure greatly improves the convergence of both algorithms.
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Duarte Jr., Elias Procópio, e Andréa Weber. "Simulation of a Distributed Connectivity Algorithm for General Topology Networks". In Workshop de Testes e Tolerância a Falhas. Sociedade Brasileira de Computação - SBC, 2002. http://dx.doi.org/10.5753/wtf.2002.23409.
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The Distributed Network Connectivity algorithm allows every node in a general topology network to determine to which portions of the network it is connected, and which portions are unreachable. The algorithm consists of three phases: test, dissemination, and connectivity computation. During the testing phase each fault-free node tests all its neighbors at each testing interval. Upon the detection of a new fault event, the tester starts the dissemination phase, in which a reliable broadcast algorithm is employed to inform the other connected nodes about the event. At any time, any working node may run the third phase, in which a graph connectivity algorithm shows the complete network connectivity. Extensive simulation results are presented, considering various topologies such as the hypercube and random graphs. Results are compared to those of other algorithms.
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Zhang, Zhuoqun, e Andrew M. Maiden. "A comparison of ptychographic phase retrieval algorithms". In Quantitative Phase Imaging V, editado por Gabriel Popescu e YongKeun Park. SPIE, 2019. http://dx.doi.org/10.1117/12.2508157.
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Gao, Yunhui, e Liangcai Cao. "Numerical algorithms for pixel super-resolution holographic imaging". In Quantitative Phase Imaging VIII, editado por Gabriel Popescu, YongKeun Park e Yang Liu. SPIE, 2022. http://dx.doi.org/10.1117/12.2608219.
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Li, Sirui, e Huazhou Li. "A Robust Four-Phase Equilibrium Calculation Algorithm for Hydrocarbon-Water Mixtures at Pressure and Enthalpy Specifications". In SPE Western Regional Meeting. SPE, 2023. http://dx.doi.org/10.2118/213018-ms.
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Abstract A robust multiphase equilibrium calculation algorithm with pressure and enthalpy (PH) specifications, i.e., an isenthalpic algorithm, plays an important role in the compositional simulations of steam-based enhanced oil recovery (EOR) applications (such as steam and solvent co-injection process for heavy oil recovery). Up to now, there are few works documented in the literature focusing on four-phase isenthalpic algorithms. In this paper, we propose a four-phase isenthalpic algorithm with a nested approach. It contains an inner loop and an outer loop. In the inner loop, a well-designed isobaric/isothermal (PT) multiphase (up to four phases) equilibrium algorithm is employed to solve the phase fractions and compositions, while the Brent's method (1971) is applied in the outer loop to update the temperature by satisfying the energy conservation equation. We test the performance of the proposed algorithm using four case studies under different pressure-enthalpy conditions. Calculation results demonstrate that the proposed PH algorithm is always able to converge to the correct phase equilibria with only tens of PT algorithm calls.
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Cao, Liangcai, e Yunhui Gao. "Pixel super-resolution phase retrieval algorithms for digital holography". In Quantitative Phase Imaging IX, editado por YongKeun Park e Yang Liu. SPIE, 2023. http://dx.doi.org/10.1117/12.2655511.
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Ancora, Daniele, Diego Di Battista, Asier Marcos Vidal, Stella Avtzi, Giannis Zacharakis e Andrea Bassi. "Hidden projection tomography via phase retrieval algorithm". In Quantitative Phase Imaging VII, editado por Gabriel Popescu, YongKeun Park e Yang Liu. SPIE, 2021. http://dx.doi.org/10.1117/12.2582996.
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Liu, Wenjian, e Jinghua Li. "Development of Hybrid Genetic Algorithms for the Resource Constrained Multi-Project Scheduling Problem". In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85721.
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In multi-project environment, multiple projects share and compete for the limited resources to achieve their own goals. Besides resource constraints, there exist precedence constraints among activities within each project. This paper presents a hybrid genetic algorithm to solve the resource-constrained multi-project scheduling problem (RCMPSP), which is well known NP-hard problem. Objectives described in this paper are to minimize total project time of multiple projects. The chromosome representation of the problem is based on activity lists. The proposed algorithm was operated in two phases. In the first phase, the feasible schedules are constructed as the initialization of the algorithm by permutation based simulation and priority rules. In the second phase, this feasible schedule was optimized by genetic algorithm, thus a better approximate solution was obtained. Finally, after comparing several different algorithms, the validity of proposed algorithm is shown by a practical example.
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Opiyo, Eliab Z., Imre Horva´th e Joris S. M. Vergeest. "Case Studies on the Application of the Abstract Prototyping Strategy in the Development of Design Support Software". In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/cie-34405.
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The traditional software process models are used in the development of design support software (DSS). They are typically multi phased, and consist of requirements specification, design, implementation, testing and operation as the main phases. One of the goals of phased development is to minimize faults in the delivered codes. Many of the faults can be traced back to the pre implementation phases of requirements specification and design. Reviews are typically performed to remove faults before the requirements or designs are passed to the subsequent phase. The problem is that activities in the phases of software process models, in particular the design phase are coarsely defined and do not scale to precisely match the underlying needs. We have developed a computer based pre-implementation testing methodology called abstract prototyping. It extends the current practices by defining the steps of the design phase of the DSS development process as definition of features, creation or selection of theories, formulation of methods, building of algorithms and implementation of pilot prototypes. Based on this methodology, faults can be traced back to the requirements, theories, methods, algorithms, or pilot prototypes rather than exclusively to the requirements or designs. Under this procedure, reviews are performed to remove faults before the requirements, theories, methods, algorithms, or pilot prototypes are passed to the subsequent stage or phase. Prototypes are used to provide the feel and the look of these work products and specially designed measures are used to estimate the extent to which they fulfill their respective specification requirements. We have applied our methodology to several application cases. The results show that the levels of fulfillment of requirements for theories, methods, algorithms, or pilot prototypes can effectively be estimated and in so doing faults detected sufficiently. In this paper, we first review the problem and present the related works. We then briefly introduce the abstract prototyping concept and present its application case studies.
Relatórios de organizações sobre o assunto "Algorithmes à phases"
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Cordeiro de Amorim, Renato. A survey on feature weighting based K-Means algorithms. Web of Open Science, dezembro de 2020. http://dx.doi.org/10.37686/ser.v1i2.79.
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In a real-world data set there is always the possibility, rather high in our opinion, that different features may have different degrees of relevance. Most machine learning algorithms deal with this fact by either selecting or deselecting features in the data preprocessing phase. However, we maintain that even among relevant features there may be different degrees of relevance, and this should be taken into account during the clustering process. With over 50 years of history, K-Means is arguably the most popular partitional clustering algorithm there is. The first K-Means based clustering algorithm to compute feature weights was designed just over 30 years ago. Various such algorithms have been designed since but there has not been, to our knowledge, a survey integrating empirical evidence of cluster recovery ability, common flaws, and possible directions for future research. This paper elaborates on the concept of feature weighting and addresses these issues by critically analysing some of the most popular, or innovative, feature weighting mechanisms based in K-Means
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Kats J. M. ALGORITHMS FOR RECOVERING PHASE DENSITY. Office of Scientific and Technical Information (OSTI), maio de 1991. http://dx.doi.org/10.2172/1151257.
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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan e Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), dezembro de 2015. http://dx.doi.org/10.55274/r0010891.
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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform lighting conditions. In the second part of the framework, the context-based segmentation is developed to eliminate regions from imagery that are not considered to be a threat to the pipeline. Context based segmentation makes use of a cascade of pre-trained classifiers to search for regions that are not threats. The context based segmentation algorithm accelerates threat identification and improves object detection rates. The last phase of the framework is an efficient object detection model. Efficient object detection �follows a three-stage approach which includes extraction of the local phase in the image and the use of local phase characteristics to locate machinery threats. The local phase is an image feature extraction technique which partially removes the lighting variance and preserves the edge information of the object. Multiple orientations of the same object are matched and the correct orientation is selected using feature matching by histogram of local phase in a multi-scale framework. The classifier outputs locations of threats to pipeline.�The advanced automatic image analysis system is intended to be capable of detecting construction equipment along the ROW of pipelines with a very high degree of accuracy in comparison with manual threat identification by a human analyst. �
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Draelos, Timothy J., Stephen Heck, Jennifer Galasso e Ronald Brogan. Seismic Phase Identification with Speech Recognition Algorithms. Office of Scientific and Technical Information (OSTI), setembro de 2018. http://dx.doi.org/10.2172/1474260.
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Martinis, John M., Alexander Korotkov, Frank Wilhelm e Andrew Cleland. Multi-Qubit Algorithms in Josephson Phase Qubits. Fort Belvoir, VA: Defense Technical Information Center, novembro de 2015. http://dx.doi.org/10.21236/ada631621.
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Morkun, Vladimir S., Natalia V. Morkun e Andrey V. Pikilnyak. Augmented reality as a tool for visualization of ultrasound propagation in heterogeneous media based on the k-space method. [б. в.], fevereiro de 2020. http://dx.doi.org/10.31812/123456789/3757.
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For programming the AR tools, interactive objects and creating the markers, the method of fiber spaces (k-space) for modeling of ultrasonic wave propagation in an inhomogeneous medium using coarse grids, with maintaining the required accuracy was used. The algorithm and tools of augmented reality were introduced into the adaptive control system of the pulp gas phase in the iron ore flotation process using a control action on the basis of high-energy ultrasound dynamic effects generated by ultrasonic phased arrays. The tools of augmented reality based on k-space methods allow to facilitate wider adoption of ultrasound technology and visualize the ultra-sound propagation in heterogeneous media by providing a specific correspondence between the ultrasound data acquired in real- time and a sufficiently detailed augmented 3D scene. The tools of augmented reality allow seeing the field of ultrasound propagation, its characteristics, as well as the effect of the dynamic effects of ultrasound on the change in the gas phase during the flotation process.
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Gavel, D. Fast algorithms for calculating laser wavefront phase compensation given noisy measurements of phase gradient. Office of Scientific and Technical Information (OSTI), setembro de 1989. http://dx.doi.org/10.2172/7272996.
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Eichel, P. H. The phase gradient autofocus algorithm: An optimal estimator of the phase derivative. Office of Scientific and Technical Information (OSTI), setembro de 1989. http://dx.doi.org/10.2172/5609345.
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Carroll, James V. Algorithms for Robust Identification and Control of Large Space Structures. Phase 1. Fort Belvoir, VA: Defense Technical Information Center, maio de 1988. http://dx.doi.org/10.21236/ada198130.
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Ciezki, John G., e Robert W. Ashton. PEBB Feedback Control Low Library. Volume 1: Three-Phase Inverter Control Algorithms. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1999. http://dx.doi.org/10.21236/ada360711.
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