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检索条件"任意字段=International Workshop on Multilevel Optimization - Algorithms and Applications"

共 1021 条记录，以下是131-140 订阅

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Proceedings of the 12th international workshop on Programming Models and applications for Multicores and Manycores, PMAM 2021

Proceedings of the 12th International Workshop on Programmin...

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12th international workshop on Programming Models and applications for Multicores and Manycores, PMAM 2021

ISBN: (纸本)9781450383486

The proceedings contain 3 papers. The topics discussed include: a new generation of task-parallel algorithms for matrix inversion in many-threaded CPUs;CompactNet: platform-aware automatic optimization for convolutional neural networks;and porting and evaluation of a distributed task-driven stencil-based application.

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An Optimizing multilevel Thresholding for Image Segmentation Based on Hybrid Swarm Computation optimization 16th

An Optimizing Multilevel Thresholding for Image Segmentation...

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16th international Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th international Conference on Frontiers of Information Technology, applications and Tools, FITAT 2020

作者： Dao, Thi-Kien Wang, Hong-Jiang Yu, Jie Nguyen, Huu-Quynh Ngo, Truong-Giang Nguyen, Trong-The Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Mechanical and Automotive Engineering Fujian University of Technology Fuzhou350118 China Faculty of Computer Science and Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Department of Information Technology Haiphong University of Management and Technology Haiphong Viet Nam

ISBN: (纸本)9789813367562

This paper suggests a solution for the image segmentation (IS) problem with the multilevel thresholding based on one of the latest hybrid swarm computation optimization algorithms, particle swarms, and gravitational search (PSGA). The experimental results are comparable with other state-of-the-art algorithms that show that the PSGA on selected images is better than the competitors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Image segmentation

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2009 international workshop on Intelligent Systems and applications, ISA 2009

2009 International Workshop on Intelligent Systems and Appli...

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2009 international workshop on Intelligent Systems and applications, ISA 2009

ISBN: (纸本)9781424438945

The proceedings contain 634 papers. The topics discussed include: a gait recognition method based on KFDA and SVM;a general QoS-aware service composition model for ubiquitous computing;a hybrid approach of path planning for mobile robots based on the combination of ACO and APF algorithms;a hybrid genetic algorithm with hyper-mutation and elitist strategies for automated analog circuit design;a hybrid particle swarm optimization algorithm for multimodal function optimization;an algorithm of coalition structure generation with given required bound based on cardinality structure;an adaptive weighted support vector machine;an adaptive repulsive particle swarm optimization for make span and maximum lateness minimization in the permutation flowshop scheduling problem;and an adaptive clonal selection algorithm and its applications.

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MULTI-AGENT ASYNCHRONOUS NONCONVEX LARGE-SCALE optimization 7

MULTI-AGENT ASYNCHRONOUS NONCONVEX LARGE-SCALE OPTIMIZATION

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7th IEEE international workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

作者： Cannelli, L. Facchinei, F. Scutari, G. Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA Univ Roma La Sapienza Dept Comp Control & Management Engn Rome Italy

ISBN: (纸本)9781538612514

We propose a novel algorithmic framework for the asynchronous and distributed optimization of multi-agent systems. We consider the constrained minimization of a nonconvex and nonsmooth partially separable sum-utility function, i.e., the cost function of each agent depends on the optimization variables of that agent and of its neighbors. This partitioned setting arises in several applications of practical interest. The proposed algorithmic framework is distributed and asynchronous: i) agents update their variables at arbitrary times, without any coordination with the others;and ii) agents may use outdated information from their neighbors. Convergence to stationary solutions is proved, and theoretical complexity results are provided, showing nearly ideal linear speedup with respect to the number of agents, when the delays are not too large.

关键词： Asynchronous algorithms big-data problems multi-agent nonconvex optimization linear speedup

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The Sixth international workshop on Automatic Performance Tuning (iWAPT2011)

The Sixth International Workshop on Automatic Performance Tu...

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international Conference on Computational Science (ICCS) on the Ascent of Computational Excellence

作者： Katagiri, Takahiro Vuduc, Richard Univ Tokyo Ctr Informat Technol Bunkyo Ku 2-11-16 Yayoi Tokyo 1138658 Japan Georgia Inst Technol Sch Comp Sci & Engn Atlanta GA 30332 USA

This preface summarizes The Sixth international workshop on Automatic Performance Tuning (iWAPT2011).

关键词： Performance modeling Adaptive algorithms Numerical algorithms and libraries Scientific applications Parallel and distributed computing Computing with GPGPU and accelerators Database management system Numerical precision and stability Resource restrictions (real-time, memory etc.) Empirical Compilation Automatically-tuned Code Generation Frameworks and theories of automatic tuning and software optimization Autonomic computing and context-aware computing Low-power computing and green computing Position papers

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Utilization-controlled Task Consolidation for Power optimization in Multi-Core Real-Time Systems

Utilization-controlled Task Consolidation for Power Optimiza...

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1st international workshop on Cyber-Physical Systems, Networks, and applications (CPSNA) held during 17th IEEE international Conference on Embedded and Real-Time Computing Systems and applications (RTCSA)

作者： Fu, Xing Wang, Xiaorui Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

ISBN: (纸本)9780769545028

Since multi-core processors have become a primary trend in processor development, new scheduling algorithms are needed to minimize power consumption while achieving the desired timeliness guarantees for multi-core (and many-core) real-time embedded systems. Although various power/energy-efficient scheduling algorithms have recently been proposed, existing studies may have degraded run-time performance in terms of power/energy efficiency and real-time guarantees when applied to real-time embedded systems with uncertain execution times. In this paper, we propose a novel online solution that integrates core-level feedback control with processor-level optimization to minimize both the dynamic and leakage power consumption of a multi-core real-time embedded system. Our solution monitors the utilization of each CPU core in the system and dynamically responds to unpredictable execution time variations by conducting per-core voltage and frequency scaling. We then perform task consolidation on a longer timescale and shut down unused cores for maximized power savings. Both empirical results on a hardware multi-core testbed with well-known benchmarks and simulation results in many-core systems show that our solution provides the desired real-time guarantees while achieving more power savings than three state-of-the-art algorithms.

关键词： Multicore processing Real time systems Power demand optimization Embedded systems Resource management Frequency control

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Realization of n-D signal processing tasks in high-speed applications

Realization of n-D signal processing tasks in high-speed app...

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4th international workshop on Multidimensional Systems (NDS 2005)

作者： Velten, J Krips, M Kummert, A Univ Wuppertal D-42119 Wuppertal Germany

ISBN: (纸本)3981029984

The present paper describes initial aspects of a framework for realization of n-D signal processing tasks under rigorous budgetary demands, as usually found in industrial applications. Besides design on the basis of adequate guidelines, development of algorithms with respect to a dedicated hardware platform is an important means of optimization. An exemplary realization of a hand detection device is presented, which incorporates several efficient algorithms that are limited in accuracy but in combination lead to a robust hand detection algorithm. These basic processing blocks are mainly based on FPGA realizations of well known FIR filter structures in combination with convolution-like operations based on Boolean logic instead of complex arithmetic. One example for this class of algorithms is binary morphology, which can be realized in low-cost FPGAs for high data throughput of several Gpixel per second and with large operator masks, e.g. with 25x25 pixels in size.

关键词： Digital signal processing

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Comparison of various encoding schemes for tree in Biobjective optimization scenario

Comparison of various encoding schemes for tree in Biobjecti...

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4th international workshop on Soft Computing applications, SOFA 2010

作者： Sanger, Amit Kumar Singh Singh, Pramod Kumar ABV Indian Institute of Information Technology and Management Gwalior India

ISBN: (纸本)9781424479849

To find MST (Minimum Spanning Trees) in complete graph is a classical problem in operation research having network design as an important application. It is possible to solve MST problem efficiently, but its Biobjective versions are NP hard. In this paper, we present a comparison of two encoding schemes for representing tree in Biobjective optimization scenario. The three different instances of Biobjective MST have been solved by using two different encoding methods in the evolutionary algorithms;Pareto optimal front obtained has been taken into account for comparative study. Our evolutionary computation approach involves Biobjective MST problem using NSGAII (Nondominated Sorting Genetic Algorithm II) approach. We compare edge sets encoding with Prüfer encoding in evolutionary algorithm for Biobjective MST, we find edge sets encoding outperforms the Prüfer in Biobjective optimization scenario. © 2010 IEEE.

关键词： Genetic algorithms

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Evolutionary optimization on Artificial Neural Networks for Predicting the User's Future Semantic Location 20th

Evolutionary Optimization on Artificial Neural Networks for ...

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20th international Conference on Engineering applications of Neural Networks (EANN) /1st international workshop on Pervasive Intelligence (PEINT)

作者： Karatzoglou, Antonios Robert Bosch Advance Engn Chassis Syst Control Abstatt Germany

ISBN: (纸本)9783030202576;9783030202569

Location prediction has gained enormously in importance in the recent years. For this reason, there exists a great variety of research work carried out at both the academia and the industry. At the same time, there is an increasing trend towards utilizing additional semantic information aiming at building more accurate algorithms. Existing location prediction approaches rely mostly on data-driven models, such as Hidden Markov Chains, Bayes Networks and Artificial Neural Networks (ANN), with the latter achieving usually the best results. Most ANN-based solutions apply Grid Parameter Search and Stochastic Gradient Descent for training their models, that is, for identifying the optimal structure and weights of the network. In this work, motivated by the promising results of genetic algorithms in optimizing neural networks in temporal sequence learning areas, such as the gene and the stock price index prediction, we propose and evaluate their use in optimizing our ANN-based semantic location prediction model. It can be shown that evolutionary algorithms can lead to a significant improvement with respect to its predictive performance, as well as to the time needed for the model's optimization.

关键词： Evolutionary algorithms Artificial Neural Networks Semantic trajectories Semantic location prediction

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The research on the matching design of the ship-engine-propeller based on multi-objective particle swarm optimization

The research on the matching design of the ship-engine-prope...

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2nd international workshop on Intelligent Systems and applications, ISA2010

作者： Liu, Aihua Fan, Shidong School of Energy and Power Engineering Wuhan University of Technology Wuhan China

ISBN: (纸本)9781424458745

The matching design problem of the ship-engine-propeller is a non-linear constrained multi-objective optimization problem which is performed based on multiple objectives,such as system efficiency and the life cycle cost. A multi-objective particle swarm optimization (MOPSO) approach for matching design problem of the ship-engine-propeller problem is presented in this paper.A real matching design problem of the ship-engine-propeller is employed to demonstrate applicability of the proposed *** results indicate that multi-objective particle swarm optimization approach in comparison with most of multi-objective optimization algorithms such as the multiple objective genetic algorithm (MOGA) is simple ,efficient and operable. ©2010 IEEE.

关键词： Ships

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