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检索条件"任意字段=Conference on Simulation-Driven Modeling and Optimization"

共 1171 条记录，以下是781-790 订阅

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Improving performance of cloud datacenters using heuristic driven VM migration

Improving performance of cloud datacenters using heuristic d...

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International conference on Next Generation Computing Technologies (NGCT)

作者： Jyoti Thaman Manpreet Singh Department of Computer Science & Engineering MMU Sadopur Ambala India

ISBN: (纸本)9781467368100

Cloud Computing has emerged as an alternate infrastructural, computational and service platform. It caters the users with least financial burden. Cloud uses virtualization for resource management through Virtual Machine (VM). An important aspect of cloud computing remains Quality of Service (QoS), often referred as Service Level Agreement (SLA). Several user applications simultaneously compete for resources in data centers. With limitations in available resources and compelling SLAs, VMs have to be migrated live during execution. Another concern in Clouds remains energy efficiency because of huge sized servers and communication requirements; most of the investment goes in power. In this paper, a novel SLA conscious variance based VM Selection scheme has been proposed. simulation results revels that proposed scheme outperforms other approaches based on resource optimization for cloud computing environments. During simulation some real world workload traces from PlanetLab has been used.

关键词： Cloud computing Servers Resource management Computational modeling Load modeling Energy consumption Reactive power

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A scalable approach for data-driven taxi ride-sharing simulation

A scalable approach for data-driven taxi ride-sharing simula...

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IEEE International conference on Big Data

作者： Masayo Ota Huy Vo Claudio Silva Juliana Freire Department of Computer Science and Engineering New York University Department of Computer Science The City College of the City University of New York

As urban population grows, cities face many challenges related to transportation, resource consumption, and the environment. Ride sharing has been proposed as an effective approach to reduce traffic congestion, gasoline consumption, and pollution. Despite great promise, researchers and policy makers lack adequate tools to assess tradeoffs and benefits of various ride-sharing strategies. Existing approaches either make unrealistic modeling assumptions or do not scale to the sizes of existing data sets. In this paper, we propose a real-time, data-driven simulation framework that supports the efficient analysis of taxi ride sharing. By modeling taxis and trips as distinct entities, our framework is able to simulate a rich set of realistic scenarios. At the same time, by providing a comprehensive set of parameters, we are able to study the taxi ride-sharing problem from different angles, considering different stakeholders' interests and constraints. To address the computational complexity of the model, we describe a new optimization algorithm that is linear in the number of trips and makes use of an efficient indexing scheme, which combined with parallelization, makes our approach scalable. We evaluate our framework and algorithm using real data - 360 million trips taken by 13,000 taxis in New York City during 2011 and 2012. The results demonstrate that our framework is effective and can provide insights into strategies for implementing city-wide ride-sharing solutions. We describe the findings of the study as well as a performance analysis of the model.

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Multidisciplinary design optimization for a high-resolution earth-imaging constellation

Multidisciplinary design optimization for a high-resolution ...

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IEEE conference on Aerospace

作者： Michael Curry Paul La Tour Stefan Slagowski Massachusetts Institute of Technology Cambridge MA The Charles Stark Draper Laboratory Inc. Cambridge MA

Imaging of the Earth's surface is a desired capability for many applications and problem domains. Space-based systems provide a unique platform that can provide persistent coverage over a wide region and have many advantages over atmospheric systems. The case study described here starts with the development of a concise mission statement for an affordable constellation of high-resolution Earth imaging satellites. The problem is modeled using integrated multidisciplinary analysis modules that were validated through simulation and comparison to three known real-world systems. Through multiple techniques, a Pareto Front of non-dominated designs is identified. Two candidate designs, which are on the Pareto front and balance the cost versus performance trade-off, are identified through two different heuristic optimization methods; simulated annealing and genetic algorithms. Key trades are shown to be primarily driven by design variables for optical aperture size, the number of satellites per orbital plane, and the number of orbital planes in the constellation. This can further be shown to create three distinct design regions primarily characterized by the number of satellites in the constellation.

关键词： Satellites Earth Computational modeling Analytical models Data models Imaging Apertures

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TOWARD A MODEL-driven ENGINEERING FRAMEWORK FOR REPRODUCIBLE simulation EXPERIMENT LIFECYCLE MANAGEMENT

TOWARD A MODEL-DRIVEN ENGINEERING FRAMEWORK FOR REPRODUCIBLE...

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Winter simulation conference

作者： Teran-Somohano, Alejandro Dayibas, Orcun Yilmaz, Levent Smith, Alice Auburn Univ Ind & Syst Engn Auburn AL 36849 USA Middle East Tech Univ Dept Comp Engn Ankara Turkey Auburn Univ Comp Sci & Software Engn Auburn AL 36849 USA

ISBN: (纸本)9781479974863

Goal-directed reproducible experimentation with simulation models is still a significant challenge. The underutilization of design of experiments, limited transparency in the collection and analysis of results, and ad-hoc adaptation of experiments as learning takes place continue to hamper reproducibility and hence cause a credibility gap. In this study, we propose a strategy that leverages the synergies between model-driven engineering, intelligent agent technology, and variability modeling to support the management of the lifecycle of a simulation experiment. Experiment design and workflow models are introduced for configurable experiment synthesis and execution. Feature-based variability modeling is used to design a family of experiments, which can be leveraged by ontology-driven software agents to configure, execute, and reproduce experiments. Online experiment adaptation is proposed as a strategy to facilitate dynamic experiment model updating as objectives shift from validation to variable screening, understanding, and optimization.

关键词： design of experiments digital simulation ontologies (artificial intelligence) software agents configurable experiment execution configurable experiment synthesis feature-based variability modeling intelligent agent technology model-driven engineering framework ontology-driven software agents reproducible simulation experiment lifecycle management workflow models Adaptation models Analytical models Computational modeling Data models Educational institutions Intelligent agents Intelligent agents Experimental Design data models Digital simulation Computer simulation Educational institutions ANALYSIS MODELS Computational modeling Life cycle Model driven engineering Adaptation models simulation test

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CLASSIFICATION AIDED DOMAIN REDUCTION FOR HIGH DIMENSIONAL optimization

CLASSIFICATION AIDED DOMAIN REDUCTION FOR HIGH DIMENSIONAL O...

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Winter simulation conference

作者： Singh, Prashant Ferranti, Francesco Deschrijver, Dirk Couckuyt, Ivo Dhaene, Tom Ghent Univ iMinds Dept Informat Technol ( INTEC) Gaston Crommenlaan 8 B-9050 Ghent Belgium

ISBN: (纸本)9781479974863

Engineering design optimization often involves computationally expensive time consuming simulations. Although surrogate-based optimization has been used to alleviate the problem to some extent, surrogate models (like Kriging) struggle as the dimensionality of the problem increases to medium-scale. The enormity of the design space in higher dimensions (above ten) makes the search for optima challenging and time consuming. This paper proposes the use of probabilistic support vector machine classifiers to reduce the search space for optimization. The proposed technique transforms the optimization problem into a binary classification problem to differentiate between feasible (likely containing the optima) and infeasible (not likely containing the optima) regions. A model-driven sampling scheme selects batches of probably-feasible samples while reducing the search space. The result is a reduced subspace within which existing optimization algorithms can be used to find the optima. The technique is validated on analytical benchmark problems.

关键词： CAD pattern classification sampling methods support vector machines Kriging model binary classification problem classification aided domain reduction engineering design optimization model-driven sampling scheme optimization problem probabilistic support vector machine classifiers search space reduction surrogate model surrogate-based optimization Algorithm design and analysis Computational modeling optimization Probabilistic logic Support vector machines Training Vectors Support Vector Network Algorithm design and analysis Probabilistic logic Pattern recognition sampling methods Computational modeling Optimal design Functional training optimization algorithms

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A Novel PSIM and Matlab Co-simulation Approach to Particle Swarm optimization Tuning of PID Controllers

A Novel PSIM and Matlab Co-Simulation Approach to Particle S...

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International conference on optimization of Electrical and Electronic Equipment (OPTIM)

作者： Darvill, John Tisan, Alin Cirstea, Marcian Anglia Ruskin Univ Cambridge England

ISBN: (纸本)9781479951833

Particle swarm optimization (PSO) has proven to be a particularly popular evolutionary algorithm for the tuning of PID controllers, due to its relative simplicity and suitability as a function approximator. This paper presents a new modeling technique, featuring co-simulation between Matlab and PSIM, a specialist control and power electronics simulation environment. The tuned PID is applied to a buck converter, driven by a PV cell. The novel solution is compared with and evaluated against a system which is tuned using a traditional method. The simulation results indicate that the controller developed using the PSO algorithm achieves a faster response time without adversely affecting peak errors. There are added benefits of this new approach, in terms of a shorter time scale for conceptual model development.

关键词： Equations Inductors Integrated circuit modeling MATLAB Mathematical model Photovoltaic cells Tuning

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Phase-Spacing optimization of Linear Microstrip Antenna Arrays By EM-Based Superposition Models 10

Phase-Spacing Optimization of Linear Microstrip Antenna Arra...

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Loughborough Antennas and Propagation conference (LAPC)

作者： Koziel, Slawomir Ogurtsov, Stanislav Reykjavik Univ Engn Optimizat & Modeling Ctr Menntavegur 1 IS-101 Reykjavik Iceland

ISBN: (纸本)9781479936625

A technique for simulation-driven optimization of phase excitation tapers and spacings for linear arrays of microstrip antennas is presented. It exploits two models of the array under design: an array factor-based model and a simulation-based surrogate model. The former produces an initial design. The latter is used for tuning of the array radiation response as well as for validation of the final design. The simulation-based model is constructed as a superposition of simulated responses of the array under design. Low computational costs are ensured by coarse-mesh simulations. Suitable correction is carried out with respect to the high-fidelity array model. This correction is iteratively performed in the optimization process. Our technique is demonstrated with radiation response synthesis of linear arrays comprising thirty two microstrip patch antennas by phase-spacing optimization.

关键词： linear antenna array radiation pattern surrogate-based optimization (SBO) simulation-based model superposition

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COMPARING STANDARDS AND POLICIES FOR SUSTAINABILITY IN TOLERANCE optimization

COMPARING STANDARDS AND POLICIES FOR SUSTAINABILITY IN TOLER...

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ASME International Design Engineering Technical conferences and Computers and Information in Engineering conference (IDETC/CIE)

作者： Hoffenson, Steven Soderberg, Rikard Chalmers Univ Technol Dept Prod & Prod Dev S-41296 Gothenburg Sweden

ISBN: (纸本)9780791855911

Design for sustainability often considers three potentially competing objectives in economic, ecological, and social sustainability. In general, business success hinges on economic sustainability, while ecological and social concerns are treated as secondary objectives for marketing or political purposes. Previous research has shown that there is a tradeoff among these sustainability objectives regarding design decisions that include tolerances and material choices, and different market- or policy-driven incentives may result in different optimal design decisions. This study presents and demonstrates an approach for evaluating legislative opportunities that may internalize ecological and social objectives into the economic objectives of product-developing firms, using the case study of an automotive body panel. modeling and simulation tools from Computer Aided Tolerancing (CAT), Life Cycle Assessment (LCA), and design optimization are combined using a novel framework to show how sustainability-driven government policies such as taxation may influence design decisions and sustainability outcomes.

关键词： simulation optimization modeling Performance Sustainable development Design Public policy Tradeoffs Life cycle assessment Computer-aided engineering Hinges Sustainability

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Expedited Design optimization of Compact Microwave Structures Using Adjoint Sensitivities and Space Mapping

Expedited Design Optimization of Compact Microwave Structure...

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IEEE MTT-S International conference on Numerical Electromagnetic and Multiphysics modeling and optimization

作者： Slawomir Koziel Adrian Bekasiewicz Leifur Leifsson Engineering Optimization and Modeling Center Reykjavik University Department of Aerospace Engineering Iowa State University

ISBN: (纸本)9781479968121

Expedited design optimization of compact microwave structures using adjoint sensitivities and space mapping (SM) is proposed. For the sake of computational efficiency and good generalization capability, we utilize coarse-discretization electromagnetic (EM) simulation models which are suitably corrected using SM. The mapping parameters are evolving together with the design itself (no fully converged SM parameter extraction is executed), which results in a small number of both low- and high-fidelity EM simulations throughout the optimization process. The algorithm is applied to the design of a compact rat-race coupler.

关键词： Compact microwave structures simulation-driven design Adjoint sensitivities Space mapping Surrogate-based optimization

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Research on Model-driven simulation Approach for Healthcare Information System

Research on Model-Driven Simulation Approach for Healthcare ...

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2015 International conference on Artificial Intelligence and Industrial Engineering(AIIE 2015)

作者： L.L.Song X.Q.Guo C.Wang Wuhan General Hospital of Guangzhou Command 75709th troops of Chinese People's Liberation Army

ISBN: (纸本)9781510806450

The project has studied the model-driven simulation approach for healthcare information integration system design analysis and optimization, which includes simulation model specification design, transformation of reference information model(RIM) to simulation model, and integrated simulation supporting framework. simulation model specification is studied and formulated based on simulation model portability 2.0(SMP2) to extend healthcare information system development methodology(HDF) and enhance the simulation modeling ability;Transformation of RIM to SMP2 platform-independent simulation model, modeling tools and codes(or code framework) automatically generation is implemented based on meta-modeling technique to realize the simulation model automatic or semiautomatic generation. Finally, the executable simulation approach for healthcare information system is realized.

关键词： healthcare information system simulation framework model-driven HDF SMP2

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