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Artigos de revistas sobre o assunto "Multiscale optimization"
Xu, Fan, Peter Wai Tat TSE, Yan-Jun Fang e Jia-Qi Liang. "A fault diagnosis method combined with compound multiscale permutation entropy and particle swarm optimization–support vector machine for roller bearings diagnosis". Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 233, n.º 4 (20 de julho de 2018): 615–27. http://dx.doi.org/10.1177/1350650118788929.
Texto completo da fonteMurphy, Ryan, Chikwesiri Imediegwu, Robert Hewson e Matthew Santer. "Multiscale structural optimization with concurrent coupling between scales". Structural and Multidisciplinary Optimization 63, n.º 4 (8 de janeiro de 2021): 1721–41. http://dx.doi.org/10.1007/s00158-020-02773-3.
Texto completo da fonteMjolsness, E., C. D. Garrett e W. L. Miranker. "Multiscale optimization in neural nets". IEEE Transactions on Neural Networks 2, n.º 2 (março de 1991): 263–74. http://dx.doi.org/10.1109/72.80337.
Texto completo da fonteHan, Zhenyu, Shouzheng Sun, Zhongxi Shao e Hongya Fu. "Multiscale Collaborative Optimization of Processing Parameters for Carbon Fiber/Epoxy Laminates Fabricated by High-Speed Automated Fiber Placement". Advances in Materials Science and Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/5480352.
Texto completo da fonteSivapuram, Raghavendra, Peter D. Dunning e H. Alicia Kim. "Simultaneous material and structural optimization by multiscale topology optimization". Structural and Multidisciplinary Optimization 54, n.º 5 (1 de julho de 2016): 1267–81. http://dx.doi.org/10.1007/s00158-016-1519-x.
Texto completo da fonteFritzen, Felix, Liang Xia, Matthias Leuschner e Piotr Breitkopf. "Topology optimization of multiscale elastoviscoplastic structures". International Journal for Numerical Methods in Engineering 106, n.º 6 (6 de outubro de 2015): 430–53. http://dx.doi.org/10.1002/nme.5122.
Texto completo da fonteBoucard, P. A., S. Buytet e P. A. Guidault. "A multiscale strategy for structural optimization". International Journal for Numerical Methods in Engineering 78, n.º 1 (2 de abril de 2009): 101–26. http://dx.doi.org/10.1002/nme.2484.
Texto completo da fonteZhao, Ang, Pei Li, Yehui Cui, Zhendong Hu e Vincent Beng Chye Tan. "Multiscale topology optimization with Direct FE2". Computer Methods in Applied Mechanics and Engineering 419 (fevereiro de 2024): 116662. http://dx.doi.org/10.1016/j.cma.2023.116662.
Texto completo da fonteOliveira, D. F., e A. C. Reynolds. "Hierarchical Multiscale Methods for Life-Cycle-Production Optimization: A Field Case Study". SPE Journal 20, n.º 05 (20 de outubro de 2015): 896–907. http://dx.doi.org/10.2118/173273-pa.
Texto completo da fontePal, Saloni, Richard Clare, Andrew Lambert e Stephen Weddell. "Multiscale optimization of the geometric wavefront sensor". Applied Optics 60, n.º 25 (23 de agosto de 2021): 7536. http://dx.doi.org/10.1364/ao.423536.
Texto completo da fonteTeses / dissertações sobre o assunto "Multiscale optimization"
Lalanne, Jean-Benoît. "Multiscale dissection of bacterial proteome optimization". Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/130217.
Texto completo da fonteCataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 315-348).
The quantitative composition of proteomes results from biophysical and biochemical selective pressures acting under system-level resource allocation constraints. The nature and strength of these evolutionary driving forces remain obscure. Through the development of analytical tools and precision measurement platforms spanning biological scales, we found evidence of optimization in bacterial gene expression programs. We compared protein synthesis rates across distant lineages and found tight conservation of in-pathway enzyme expression stoichiometry, suggesting generic selective pressures on expression setpoints. Beyond conservation, we used high-resolution transcriptomics to identify numerous examples of stoichiometry preserving cis-elements compensation in pathway operons. Genome-wide mapping of transcription termination sites also led to the discovery of a phylogenetically widespread mode of bacterial gene expression, 'runaway transcription', whereby RNA polymerases are functionally uncoupled from pioneering ribosomes on mRNAs. To delineate biophysical rationales underlying these pressures, we formulated a parsimonious ribosome allocation model capturing the trade-off between reaction flux and protein production cost. The model correctly predicts the expression hierarchy of key translation factors. We then directly measured the quantitative relationship between expression and fitness for specific translation factors in the Gram-positive species Bacillus subtilis. These precision measurements confirmed that endogenous expression maximizes growth rate. Idiosyncratic transcriptional changes in regulons were however observed away from endogenous expression. The resulting physiological burdens sharpened the fitness landscapes. Spurious system-level responses to targeted expression perturbations, called 'regulatory entrenchment', thus exacerbate the requirement for precisely set expression stoichiometry.
by Jean-Benoît Lalanne.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Physics
Fitriani. "Multiscale Dynamic Time and Space Warping". Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45279.
Texto completo da fonteIncludes bibliographical references (p. 149-151).
Dynamic Time and Space Warping (DTSW) is a technique used in video matching applications to find the optimal alignment between two videos. Because DTSW requires O(N4) time and space complexity, it is only suitable for short and coarse resolution videos. In this thesis, we introduce Multiscale DTSW: a modification of DTSW that has linear time and space complexity (O(N)) with good accuracy. The first step in Multiscale DTSW is to apply the DTSW algorithm to coarse resolution input videos. In the next step, Multiscale DTSW projects the solution from coarse resolution to finer resolution. A solution for finer resolution can be found effectively by refining the projected solution. Multiscale DTSW then repeatedly projects a solution from the current resolution to finer resolution and refines it until the desired resolution is reached. I have explored the linear time and space complexity (O(N)) of Multiscale DTSW both theoretically and empirically. I also have shown that Multiscale DTSW achieves almost the same accuracy as DTSW. Because of its efficiency in computational cost, Multiscale DTSW is suitable for video detection and video classification applications. We have developed a Multiscale-DTSW-based video classification framework that achieves the same accuracy as a DTSW-based video classification framework with greater than 50 percent reduction in the execution time. We have also developed a video detection application that is based on Dynamic Space Warping (DSW) and Multiscale DTSW methods and is able to detect a query video inside a target video in a short time.
by Fitriani.
S.M.
Yourdkhani, Mostafa. "Multiscale modeling and optimization of seashell structure and material". Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66991.
Texto completo da fonteUne vaste majorité des mollusques développent une coquille dure pour leur pro-tection. Une coquille typique est constitué de deux couches distinctes. La couche externe est faite de calcite (un matériau dur mais fragile), tandis que la couche in-terne est composée de nacre, un matériau plus résiliant et ductile. La nacre est un matériau biocomposite constitué de plus de 95% d'aragonite sous forme de ta-blette et d'un matériel organique souple qui forme la matrice. Bien que la cérami-que aragonite constitue une grande portion de la nacre, ses propriétés mécaniques sont étonnamment plus élevées de celles de ses constituants. La calcite et la nacre, deux matériaux avec des propriétés et des structures différentes, sont supposément étalonnées de façon optimale pour combattre les attaques de prédateurs. Cette étude cherche à déterminer les règles de construction d'une coquille de gastropode en utilisant la modélisation multi-échelle et des techniques d'optimisation. À l'échelle microscopique, un volume représentatif de la microstructure de la nacre a été utilisé pour formuler une solution analytique de son module d'élasticité et un critère de fracture multiaxial fonction des dimensions de la microstructure. À l'échelle macroscopique, un modèle d'éléments finis à deux couches de la co-quille à été utilisé pour représenter la curvature et le ratio calcite/nacre en fonction des paramètres géométriques. La charge maximale que la coquille peut supporter à son apex a été déterminée. Une approche d'optimisation multi-échelle a aussi été employée pour évaluer la reconstruction optimale du coquillage naturel. Fina-lement, plusieurs tests ont été effectués sur une coquille d'abalone rouge pour valider les résultats.
Umoh, Utibe Godwin. "Multiscale analysis of cohesive fluidization". Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/28988.
Texto completo da fonteSorrentino, Luigi. "Simulation and optimization of crowd dynamics using a multiscale model". Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/318.
Texto completo da fonteIn the last decades, the modeling of crowd motion and pedestrian .ow has attracted the attention of applied mathematicians, because of an increasing num- ber of applications, in engineering and social sciences, dealing with this or similar complex systems, for design and optimization purposes. The crowd has caused many disasters, in the stadiums during some major sporting events as the "Hillsborough disaster" occurred on 15 April 1989 at Hills- borough, a football stadium, in She¢ eld, England, resulting in the deaths of 96 people, and 766 being injured that remains the deadliest stadium-related disaster in British history and one of the worst ever international football accidents. Other example is the "Heysel Stadium disaster" occurred on 29 May 1985 when escaping, fans were pressed against a wall in the Heysel Stadium in Brussels, Belgium, as a result of rioting before the start of the 1985 European Cup Final between Liv- erpool of England and Juventus of Italy. Thirty-nine Juventus fans died and 600 were injured. It is well know the case of the London Millennium Footbridge, that was closed the very day of its opening due to macroscopic lateral oscillations of the structure developing while pedestrians crossed the bridge. This phenomenon renewed the interest toward the investigation of these issues by means of mathe- matical modeling techniques. Other examples are emergency situations in crowded areas as airports or railway stations. In some cases, as the pedestrian disaster in Jamarat Bridge located in South Arabia, mathematical modeling and numerical simulation have already been successfully employed to study the dynamics of the .ow of pilgrims, so as to highlight critical circumstances under which crowd ac- cidents tend to occur and suggest counter-measures to improve the safety of the event. In the existing literature on mathematical modeling of human crowds we can distinguish two approaches: microscopic and macroscopic models. In model at microscopic scale pedestrians are described individually in their motion by ordinary di¤erential equations and problems are usually set in two-dimensional domains delimiting the walking area under consideration, with the presence of obstacles within the domain and a target. The basic modeling framework relies on classical Newtonian laws of point. The model at the macroscopic scale consists in using partial di¤erential equations, that is in describing the evolution in time and space of pedestrians supplemented by either suitable closure relations linking the velocity of the latter to their density or analogous balance law for the momentum. Again, typical guidelines in devising this kind of models are the concepts of preferred direction of motion and discomfort at high densities. In the framework of scalar conservation laws, a macroscopic onedimensional model has been proposed by Colombo and Rosini, resorting to some common ideas to vehicular tra¢ c modeling, with the speci.c aim of describing the transition from normal to panic conditions. Piccoli and Tosin propose to adopt a di¤erent macroscopic point of view, based on a measure-theoretical framework which has recently been introduced by Canuto et al. for coordination problems (rendez-vous) of multiagent systems. This approach consists in a discrete-time Eulerian macroscopic representation of the system via a family of measures which, pushed forward by some motion mappings, provide an estimate of the space occupancy by pedestrians at successive time steps. From the modeling point of view, this setting is particularly suitable to treat nonlocal interactions among pedestrians, obstacles, and wall boundary conditions. A microscopic approach is advantageous when one wants to model di¤erences among the individuals, random disturbances, or small environments. Moreover, it is the only reliable approach when one wants to track exactly the position of a few walkers. On the other hand, it may not be convenient to use a microscopic approach to model pedestrian .ow in large environments, due to the high com- putational e¤ort required. A macroscopic approach may be preferable to address optimization problems and analytical issues, as well as to handle experimental data. Nonetheless, despite the fact that self-organization phenomena are often visible only in large crowds, they are a consequence of strategical behaviors devel- oped by individual pedestrians. The two scales may reproduce the same features of the group behavior, thus providing a perfect matching between the results of the simulations for the micro- scopic and the macroscopic model in some test cases. This motivated the multiscale approach proposed by Cristiani, Piccoli and Tosin. Such an approach allows one to keep a macroscopic view without losing the right amount of .granularity,.which is crucial for the emergence of some self-organized patterns. Furthermore, the method allows one to introduce in a macroscopic (averaged) context some micro- scopic e¤ects, such as random disturbances or di¤erences among the individuals, in a fully justi.able manner from both the physical and the mathematical perspec- tive. In the model, microscopic and macroscopic scales coexist and continuously share information on the overall dynamics. More precisely, the microscopic part tracks the trajectories of single pedestrians and the macroscopic part the density of pedestrians using the same evolution equation duly interpreted in the sense of measures. In this respect, the two scales are indivisible. Starting from model of Cristiani, Piccoli and Tosin we have implemented algo- rithms to simulate the pedestrians motion toward a target to reach in a bounded area, with one or more obstacles inside. In this work di¤erent scenarios have been analyzed in order to .nd the obstacle con.guration which minimizes the pedes- trian average exit time. The optimization is achieved using to algorithms. The .rst one is based on the exhaustive exploration of all positions: the average exit time for all scenarios is computed and then the best one is chosen. The second algorithm is of steepest descent type according to which the obstacle con.guration corresponding to the minimum exit time is found using an iterative method. A variant has been introduced to the algorithm so to obtain a more e¢ cient proce- dure. The latter allows to .nd better solutions in few steps than other algorithms. Finally we performed other simulations with bounded domains like a classical .at with .ve rooms and two exits, comparing the results of three di¤erent scenario changing the positions of exit doors. [edited by author]
X n.s.
Parno, Matthew David. "A multiscale framework for Bayesian inference in elliptic problems". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65322.
Texto completo da fontePage 118 blank. Cataloged from PDF version of thesis.
Includes bibliographical references (p. 112-117).
The Bayesian approach to inference problems provides a systematic way of updating prior knowledge with data. A likelihood function involving a forward model of the problem is used to incorporate data into a posterior distribution. The standard method of sampling this distribution is Markov chain Monte Carlo which can become inefficient in high dimensions, wasting many evaluations of the likelihood function. In many applications the likelihood function involves the solution of a partial differential equation so the large number of evaluations required by Markov chain Monte Carlo can quickly become computationally intractable. This work aims to reduce the computational cost of sampling the posterior by introducing a multiscale framework for inference problems involving elliptic forward problems. Through the construction of a low dimensional prior on a coarse scale and the use of iterative conditioning technique the scales are decouples and efficient inference can proceed. This work considers nonlinear mappings from a fine scale to a coarse scale based on the Multiscale Finite Element Method. Permeability characterization is the primary focus but a discussion of other applications is also provided. After some theoretical justification, several test problems are shown that demonstrate the efficiency of the multiscale framework.
by Matthew David Parno.
S.M.
MEJIAS, TUNI JESUS ALBERTO. "Multiscale approach applied to fires in tunnels, Model optimization and development". Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2960751.
Texto completo da fonteChen, Minghan. "Stochastic Modeling and Simulation of Multiscale Biochemical Systems". Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/90898.
Texto completo da fonteDoctor of Philosophy
Modeling and simulation of biochemical networks faces numerous challenges as biochemical networks are discovered with increased complexity and unknown mechanisms. With improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for quantitative stochastic models, or numerical models based on probability distributions, for gene and protein networks at cellular levels that match well with the data and account for randomness. This dissertation studies a stochastic model in space and time of a bacterium’s life cycle— Caulobacter. A two-dimensional model based on a natural pattern mechanism is investigated to illustrate the changes in space and time of a key protein population. However, stochastic simulations are often complicated by the expensive computational cost for large and sophisticated biochemical networks. The hybrid stochastic simulation algorithm is a combination of traditional deterministic models, or analytical models with a single output for a given input, and stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks that contain both species populations and reaction rates with widely varying magnitude. The populations of some species may become negative in the simulation under some circumstances. This dissertation investigates negative population estimates from the hybrid method, proposes several remedies, and tests them with several cases including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of observed data must be large enough to obtain valid results. To optimize system parameters, the quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic (budding) yeast life cycle model by matching different distributions between simulated results and observed data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental molecular binding mechanism by the stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different optimization strategies are explored targeting different features of the observed data.
Ahamad, Intan Salwani. "Multiscale line search in interior point methods for nonlinear optimization and applications". Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612762.
Texto completo da fonteArabnejad, Sajad. "Multiscale mechanics and multiobjective optimization of cellular hip implants with variable stiffness". Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119630.
Texto completo da fonteLa résorption osseuse et l'instabilité de l'interface os-implant sont deux goulots d'étranglement de modèles actuels d'implants orthopédiques de hanche. La résorption osseuse est souvent déclenchée par une bio-incompatibilité mécanique de l'implant avec l'os environnant. Il en résulte de graves conséquences cliniques à la fois en chirurgie primaire et en chirurgie de révision des arthroplasties de la hanche. Après la chirurgie primaire, la résorption osseuse peut entraîner des fractures périprothétiques, conduisant au descellement de l'implant. Pour la chirurgie de révision, la perte de substance osseuse compromet la capacité de l'os à bien fixer l'implant. L'instabilité de l'interface, d'autre part, se produit à la suite d'un stress excessif et de micromouvements à l'interface os-implant, ce qui empêche la fixation des implants. De ce fait, l'implant échoue, et la chirurgie de révision est nécessaire.De nombreuses études ont été réalisées pour concevoir un implant qui minimise la résorption osseuse et l'instabilité de l'interface. Cependant, les résultats n'ont pas été efficaces, car minimiser un objectif pénaliserait l'autre. En conséquence, parmi tous les modèles disponibles sur le marché, il n'y a pas d'implant qui puisse en même temps réduire ces deux objectifs contradictoires. L'objectif de cette thèse est de concevoir une prothèse orthopédique de la hanche qui puisse simultanément réduire la résorption osseuse et l'instabilité de l'implant. Nous proposons un nouveau concept d'implant à raideur variable qui est mis en œuvre grâce à l'utilisation de matériaux assemblés en treillis.Une méthodologie de conception basée sur la mécanique multi-échelle et l'optimisation multiobjectif est développé pour l'analyse et la conception d'un implant totalement poreux avec une microstructure en treillis. Les propriétés mécaniques de l'implant sont localement optimisés pour minimiser la résorption osseuse et l'instabilité d'interface. La théorie de l'homogénéisation asymptotique (HA) est utilisée pour capturer la distribution des contraintes pour l'analyse des défaillances tout le long de l'implant et de sa microstructure en treillis. Concernant cette microstructure en treillis, une bibliothèque de topologies de cellules 2D est développée, et leurs propriétés mécaniques efficaces, y compris les modules d'élasticité et la limite d'élasticité, sont calculées en utilisant le théorie HA. Puisque les prothèses orthopédiques de hanche sont généralement censées soutenir les forces dynamiques générées par les activités humaines, elles doivent être également conçues contre les fractures de fatigue pour éviter des dommages progressifs. Une méthodologie pour la conception en fatigue des matériaux cellulaires est proposée et appliquée à un implant en deux dimensions, et aux topologies de cellules carrées et de Kagome. Il est prouvé qu'un implant en treillis avec une répartition optimale des propriétés des matériaux réduit considérablement la quantité de la résorption osseuse et la contrainte de cisaillement de l'interface par rapport à un implant en titane totalement dense. La fabricabilité des implants en treillis est démontrée par la fabrication d'un ensemble de concepts de prototypes utilisant la fusion par faisceau d'électronsde poudre Ti6Al4V. La microscopie optique est utilisée pour mesurer les paramètres morphologiques de la microstructure cellulaire. L'analyse numérique et les tests de fabricabilité effectués dans cette étude préliminaire suggèrent que la méthodologie développée peut être utilisée pour la conception et la fabrication d'implants orthopédiques innovants qui peuvent contribuer de manière significative à la réduction des conséquences cliniques des implants actuels.
Livros sobre o assunto "Multiscale optimization"
Hager, William W., Shu-Jen Huang, Panos M. Pardalos e Oleg A. Prokopyev, eds. Multiscale Optimization Methods and Applications. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-29550-x.
Texto completo da fonteGünther, Michael, ed. Coupled Multiscale Simulation and Optimization in Nanoelectronics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46672-8.
Texto completo da fonteChristofides, Panagiotis D., Antonios Armaou, Yiming Lou e Amit Varshney. Control and Optimization of Multiscale Process Systems. Boston: Birkhäuser Boston, 2009. http://dx.doi.org/10.1007/978-0-8176-4793-3.
Texto completo da fonteLou. Control and Optimization of Multiscale Process Systems. Boston: Birkhäuser Boston, 2009.
Encontre o texto completo da fonteMultiscale Structural Topology Optimization. Elsevier, 2016. http://dx.doi.org/10.1016/c2015-0-01254-0.
Texto completo da fonteXia, Liang. Multiscale Structural Topology Optimization. Elsevier, 2016.
Encontre o texto completo da fonteXia, Liang. Multiscale Structural Topology Optimization. Elsevier, 2016.
Encontre o texto completo da fonteCheng, Gengdong, e Jun Yan. Multiscale Optimization and Material Design. World Scientific Publishing Co Pte Ltd, 2020.
Encontre o texto completo da fontePardalos, P. M. Multiscale Optimization Methods and Applications. Springer, 2014.
Encontre o texto completo da fontePardalos, P. M. Multiscale Optimization Methods and Applications. Springer, 2006.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Multiscale optimization"
Lewis, Robert Michael, e Stephen G. Nash. "Practical Aspects of Multiscale Optimization Methods for VLSICAD". In Combinatorial Optimization, 265–91. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3748-6_7.
Texto completo da fonteChristofides, Panagiotis D., Antonios Amaou, Yiming Lou e Amit Varsheny. "Optimization of Multiscale Process Systmes". In Control and Optimization of Multiscale Process Systems, 1–33. Boston: Birkhäuser Boston, 2008. http://dx.doi.org/10.1007/978-0-8176-4793-3_6.
Texto completo da fonteKuś, Wacław, e Tadeusz Burczyński. "Bioinspired Algorithms in Multiscale Optimization". In Advanced Structured Materials, 183–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05241-5_10.
Texto completo da fonteWang, Yanfei, e Qinghua Ma. "Iterated Adaptive Regularization for the Operator Equations of the First Kind". In Multiscale Optimization Methods and Applications, 367–77. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-29550-x_19.
Texto completo da fonteBinder, Thomas, Luise Blank, Wolfgang Dahmen e Wolfgang Marquardt. "Multiscale Concepts for Moving Horizon Optimization". In Online Optimization of Large Scale Systems, 341–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04331-8_19.
Texto completo da fonteChristofides, Panagiotis D., Antonios Amaou, Yiming Lou e Amit Varsheny. "Multiscale Process Modeling and Simulation". In Control and Optimization of Multiscale Process Systems, 1–15. Boston: Birkhäuser Boston, 2008. http://dx.doi.org/10.1007/978-0-8176-4793-3_2.
Texto completo da fonteBinder, Thomas, Luise Blank, Wolfgang Dahmen e Wolfgang Marquardt. "Iterative Multiscale Methods for Process Monitoring". In Fast Solution of Discretized Optimization Problems, 19–34. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8233-0_2.
Texto completo da fonteRamm, Ekkehard, Andrea Erhart, Thomas Hettich, Ingrid Bruss, Frédéric Hilchenbach e Junji Kato. "Damage Propagation in Composites – Multiscale Modeling and Optimization". In Multiscale Methods in Computational Mechanics, 281–304. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9809-2_15.
Texto completo da fontede Wit, Albert, e Fred van Keulen. "Framework for Multi-Level Optimization of Complex Systems". In Multiscale Methods in Computational Mechanics, 347–77. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9809-2_18.
Texto completo da fonteYuan, Xiaohui, Jing Peng e Yasumasa Nishiura. "Particle Swarm Optimization with Multiscale Searching Method". In Computational Intelligence and Security, 669–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596448_99.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Multiscale optimization"
Dong, Junjie, Ran Liu, Xiaolin Zhang e Jing Meng. "Cellular Image Segmentation Model Based on Multiscale and Attention Mechanisms". In 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS), 619–24. IEEE, 2024. http://dx.doi.org/10.1109/docs63458.2024.10704422.
Texto completo da fonteLiu, Bo feng, Haiyang Yu, Xiaojuan Hu e Yanfeng Li. "Multiscale network combined with multiloss optimization for low-light image super-resolution reconstruction". In 5th International Conference on Computer Vision and Data Mining (ICCVDM 2024), editado por Xin Zhang e Minghao Yin, 80. SPIE, 2024. http://dx.doi.org/10.1117/12.3048271.
Texto completo da fonteKakodkar, Rahul, Betsie Montano Flores, Marco De Sousa, Yilun Lin e Efstratios N. Pistikopoulos. "Towards Energy and Material Transition Integration � A Systematic Multi-scale Modeling and Optimization Framework". In Foundations of Computer-Aided Process Design, 461–68. Hamilton, Canada: PSE Press, 2024. http://dx.doi.org/10.69997/sct.171988.
Texto completo da fonteDowling, Alexander W. "Artificial Intelligence and Machine Learning for Sustainable Molecular-to-Systems Engineering". In Foundations of Computer-Aided Process Design, 22–31. Hamilton, Canada: PSE Press, 2024. http://dx.doi.org/10.69997/sct.114705.
Texto completo da fonteBonnier, N., e E. P. Simoncelli. "Locally adaptive multiscale contrast optimization". In 2005 International Conference on Image Processing. IEEE, 2005. http://dx.doi.org/10.1109/icip.2005.1529909.
Texto completo da fonteKim, Yoon Young, e Dong Hoon Jung. "Multiscale Paradigm in Genetic Algorithm". In 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-5428.
Texto completo da fonteOh, Yoonho, Myeongsu Seong, Sungchul Kim, Seonghyun Kim e Jae Gwan Kim. "Optimization of DRS-DCS system for measurement of tissue metabolism (Conference Presentation)". In Multiscale Imaging and Spectroscopy, editado por Kristen C. Maitland, Darren M. Roblyer e Paul J. Campagnola. SPIE, 2020. http://dx.doi.org/10.1117/12.2545913.
Texto completo da fonteZhai, Jingmei, e Xiao Xu. "Multiscale rough set model and optimization". In 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2010. http://dx.doi.org/10.1109/fskd.2010.5569348.
Texto completo da fonteWang, Lijun, Kaijian He, Yingchao Zou e Zhimeng Feng. "Multiscale Fractal Analysis of Electricity Markets". In 2014 Seventh International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2014. http://dx.doi.org/10.1109/cso.2014.79.
Texto completo da fonteBurblies, Andreas, Matthias Busse, Glaucio H. Paulino, Marek-Jerzy Pindera, Robert H. Dodds, Fernando A. Rochinha, Eshan Dave e Linfeng Chen. "Computer Based Porosity Design by Multi Phase Topology Optimization". In MULTISCALE AND FUNCTIONALLY GRADED MATERIALS 2006. AIP, 2008. http://dx.doi.org/10.1063/1.2896791.
Texto completo da fonteRelatórios de organizações sobre o assunto "Multiscale optimization"
Bhattacharya, Kaushik. Multiscale Modeling and Process Optimization for Engineered Microstructural Complexity. Fort Belvoir, VA: Defense Technical Information Center, outubro de 2007. http://dx.doi.org/10.21236/ada490968.
Texto completo da fonteHaile, S. M., M. Ortiz, G. Ravichandran, E. Ustandag, R. M. Murray, D. G. Godwin, K. Bhattacharya, H. A. Atwater e W. A. Goddard III. Multiscale Modeling and Process Optimization for Engineered Microstructural Complexity. Fort Belvoir, VA: Defense Technical Information Center, outubro de 2007. http://dx.doi.org/10.21236/ada572383.
Texto completo da fonteBecker, R., M. McElfresh, C. Lee, R. Balhorn e D. White. Multiscale Modeling of Nano-scale Phenomena: Towards a Multiphysics Simulation Capability for Design and Optimization of Sensor Systems. Office of Scientific and Technical Information (OSTI), dezembro de 2003. http://dx.doi.org/10.2172/15013766.
Texto completo da fonteAl-Jassim, Mowafak, e Steve Harvey. Addressing Critical Problems in Materials Science Through Multiscale and Multimode Characterization (Project 1); Characterization and Optimization of Novel Triple-Conducting Oxide Materials for Energy Applications (Project 2): Cooperative Research and Development Final Report, CRADA Number CRD-17-00711. Office of Scientific and Technical Information (OSTI), fevereiro de 2024. http://dx.doi.org/10.2172/2318703.
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