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international workshop on Intelligent Systems and applications

作者： Yang, Li-Ying School of Computer Science and Technology Xidian University Xi'an 710071 China

ISBN: (纸本)9781424498574

Pixel-level image fusion is widely used in many fields. We proposed a pixel-level image fusion algorithm based on particle swarm optimization with local search, that is, PSO-LS, which improves performance further. PSO-LS integrated the self-improvement mechanisms from memetic algorithms and can avoid local minimum in PSO. Experiments were carried out on two real world images. It is shown that fusion algorithm based on PSO-LS outperforms that based on PSO, and the former obtained optimal solution rapidly using fewer particles. © 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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2011 3rd international workshop on Intelligent Systems and applications, ISA 2011 - Proceedings

2011 3rd International Workshop on Intelligent Systems and A...

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2011 3rd international workshop on Intelligent Systems and applications, ISA 2011

ISBN: (纸本)9781424498574

The proceedings contain 214 papers. The topics discussed include: an algorithm for solving knapsack problems utilizing knowledge evolution principle;coupled direct and indirect positive feedback loop motifs induce robust synchronized bursting behaviors;chaos control of permanent magnet synchronous motor via sliding mode variable structure scheme;an improved novel kernel parameter optimization and application;modified artificial bee colony algorithms for numerical optimization;requirement analysis for data warehouses based on the tropos;selection of continuous features based on distribution of objects;analysis of reservoir slopes based on fuzzy disturbance ant-cluster algorithm;component placement process optimization for multi-head surface mounting machine based on Tabu search and improved shuffled frog-leaping algorithm;and a dynamic intrusion detection model based on immunity for wireless sensor network.

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A call for order in search space generation process of query optimization

A call for order in search space generation process of query...

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international workshop on Graph Management: Techniques and applications

作者： Nica, Anisoara Sybase SAP Company Waterloo ON Canada

ISBN: (纸本)9781424491940

Many search space generation algorithms used by query optimizers focus on efficiently and exhaustively enumerating the set of alternative plans. However, newly emerged systems, such as Object-Relational Mapping (ORM) tools, introduce new challenges to the query optimizer. This is because dynamically generated queries are very complex, relatively inexpensive to execute, and they must be optimized at runtime. For such queries the optimization time could be prohibitively expensive relative to their execution time, if traditional join enumeration algorithms are used. Recently, new heuristics for the query optimization have been proposed which provide feasible alternatives to the classical enumeration algorithms by using greedy techniques to efficiently build an execution plan. In this paper we propose a middle ground approach by introducing new techniques for dynamically ordering the search space of the candidate joins generated by conventional enumeration algorithms. Ordering the enumerated joins based on their properties allows effective pruning of the search space, so that the space size becomes adapted to the current characteristics of the optimization process. Any conventional join enumeration algorithms based on enumerating partitions and using memoization for saving access plans can be extended with our proposed ordered-Par technique. We discuss the enumeration algorithms supported in the SQL Anywhere Optimizer. We present experimental results comparing these algorithms with the new ordered-DPhyp algorithm which applies the ordered-Par technique to the DPhyp algorithm previously proposed in the research literature. © 2011 IEEE.

关键词： optimization

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Reactive power optimization based on immune genetic algorithm

Reactive power optimization based on immune genetic algorith...

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international workshop on Intelligent Systems and applications

作者： Cao, Junlong Liu, Wenying School of Electrical and Electronic Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781424498574

A modified immune genetic algorithm for power system reactive power optimization is presented. Immune factor has been added to the basic genetic algorithm, which can effectively speed up the convergence. By using the concept of entropy and the expectation of antibody in the selection operation, the algorithm can ensure the population diversity and reduce the possibility of falling into local optimum. The algorithm also uses adaptive crossover rate, mutation rate and the strategy of saving the best individual to accelerate the calculation speed meanwhile maintaining strong local search ability. Finally, the standard IEEE30 bus system simulation results show that the algorithm's accuracy and convergence are better than genetic algorithm. © 2011 IEEE.

关键词： Genetic algorithms

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Routing path determination using QoS metrics and priority based evolutionary optimization

Routing path determination using QoS metrics and priority ba...

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13th IEEE international workshop on FTDCS 2011, the 8th international Conference on ATC 2011, the 8th international Conference on UIC 2011 and the 13th IEEE international Conference on HPCC 2011

作者： Kumar, Divya Kashyap, Divya Mishra, K.K. Mishra, A.K. Department of Computer Science and Engineering MN-NIT Allahabad India

ISBN: (纸本)9780769545387

Last decade has noticed an enormous growth of Internet based information services and applications such as Email, Teleconferencing, Videophony or VoIP etc. All these applications have different QoS (Quality of Service) expectations (bandwidth, delay, jitter and reliability etc). The purpose and the benefits from these applications could be blemished if the underlying communication network does not fulfills the QoS requirements. However, different applications have different prioritized QoS requirements. Some applications put heavy demands of bandwidth, some require a more degree of reliability while some expect a negligible response time and so on. So there is always a need of routing strategy which is not only efficient and precise but guarantees the QoS measure as according to application's priorities also. Tackling the issue, this paper presents the use of priority based Evolutionary Multi-objective optimization algorithms to find the optimal routes for the data flows of various QoS classes via optimizing multiple QoS parameters namely response time, bandwidth requirements and reliability according to their importance for the application under consideration. © 2011 IEEE.

关键词： Quality of service

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Distributed convex stochastic optimization under few constraints in large networks

Distributed convex stochastic optimization under few constra...

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2011 4th IEEE international workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011

作者： Couillet, Romain Bianchi, Pascal Jakubowicz, Jérémie Centrale-Supélec-EDF Department of System Sciences and the Energy Challenge Gif sur Yvette France Institut Télécom Télécom ParisTech CNRS/LTCI France

ISBN: (纸本)9781457721052

This article introduces a distributed convex optimization algorithm in a constrained multi-agent system composed by a large number of nodes. We focus on the case where each agent seeks to optimize its own local parameter under few coupling equality and inequality constraints. The objective function is of the power flow type and can be decoupled as a sum of elementary functions, each of which assumed (imperfectly) known by only one node. Under these assumptions, a cost-efficient decentralized iterative solution based on Lagrangian duality is derived, which is provably converging. This new approach alleviates several limitations of algorithms proposed in the stochastic optimization literature. applications are proposed to decentralized power flow optimization in smart grids. © 2011 IEEE.

关键词： Multi agent systems

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An overview of the proper generalized decomposition with applications in computational rheology

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JOURNAL OF NON-NEWTONIAN FLUID MECHANICS 2011年第11期166卷 578-592页

作者： Chinesta, F. Ammar, A. Leygue, A. Keunings, R. UMR CNRS Cent Nantes EADS Corp Fdn Int Chair GEM F-44321 Nantes 3 France Arts & Metiers ParisTech F-49035 Angers 01 France Catholic Univ Louvain ICTEAM B-1348 Louvain Belgium

We review the foundations and applications of the proper generalized decomposition (PGD), a powerful model reduction technique that computes a priori by means of successive enrichment a separated representation of the unknown field. The computational complexity of the PGD scales linearly with the dimension of the space wherein the model is defined, which is in marked contrast with the exponential scaling of standard grid-based methods. First introduced in the context of computational rheology by Ammar et al. [3,4], the PGD has since been further developed and applied in a variety of applications ranging from the solution of the Schrodinger equation of quantum mechanics to the analysis of laminate composites. In this paper, we illustrate the use of the PGD in four problem categories related to computational rheology: (i) the direct solution of the Fokker-Planck equation for complex fluids in configuration spaces of high dimension, (ii) the development of very efficient non-incremental algorithms for transient problems, (iii) the fully three-dimensional solution of problems defined in degenerate plate or shell-like domains often encountered in polymer processing or composites manufacturing, and finally (iv) the solution of multidimensional parametric models obtained by introducing various sources of problem variability as additional coordinates. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Complex fluids Numerical modeling Model reduction Proper orthogonal decomposition Proper generalized decomposition Kinetic theory Parametric models optimization Inverse identification

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An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows

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COMPUTERS & OPERATIONS RESEARCH 2011年第1期38卷 287-300页

作者： Garcia-Najera, Abel Bullinaria, John A. Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

The vehicle routing problem with time windows is a complex combinatorial problem with many real-world applications in transportation and distribution logistics. Its main objective is to find the lowest distance set of routes to deliver goods, using a fleet of identical vehicles with restricted capacity, to customers with service time windows. However, there are other objectives, and having a range of solutions representing the trade-offs between objectives is crucial for many applications. Although previous research has used evolutionary methods for solving this problem, it has rarely concentrated on the optimization of more than one objective, and hardly ever explicitly considered the diversity of solutions. This paper proposes and analyzes a novel multi-objective evolutionary algorithm, which incorporates methods for measuring the similarity of solutions, to solve the multi-objective problem. The algorithm is applied to a standard benchmark problem set, showing that when the similarity measure is used appropriately, the diversity and quality of solutions is higher than when it is not used, and the algorithm achieves highly competitive results compared with previously published studies and those from a popular evolutionary multi-objective optimizer. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Vehicle routing problem Combinatorial optimization Multi-objective optimization Evolutionary algorithms

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Proceedings - 17th IEEE international Conference on Embedded and Real-Time Computing Systems and applications, RTCSA 2011

Proceedings - 17th IEEE International Conference on Embedded...

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1st international workshop on Cyber-Physical Systems, Networks, and applications, CPSNA 2011, Co-located with the 17th IEEE international Conference on Embedded and Real-Time Computing Systems and applications, RTCSA 2011

ISBN: (纸本)9780769545028

The proceedings contain 68 papers. The topics discussed include: reducing preemptions and migrations in real-time multiprocessor scheduling algorithms by releasing the fairness;mode transition for online scheduling of adaptive real-time systems on multiprocessors;utilization-controlled task consolidation for power optimization in multi-core real-time systems;a reliability enhancement mechanism for high-assurance MLC flash-based storage systems;limiting worst-case end-to-end latency when traffic increases in a switched avionics network;design and implementation of on-chip adaptive router with predictor for regional congestion;HW resource componentizing for addressing the mega-complexity of cyber-physical systems;Virtual Lock: a smartphone application for personal surveillance using camera sensor networks;dynamic activation timing configuration for product line development;and stabilization of projected image for wearable walking support system using Pico-projector.

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Energy-Aware Fixed-Priority Multi-core Scheduling for Real-Time Systems

Energy-Aware Fixed-Priority Multi-core Scheduling for Real-T...

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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： Lu, Junyang Guo, Yao Peking Univ Sch Elect Engn & Comp Sci Key Lab High Confidence Software Technol Minist Educ Beijing 100871 Peoples R China

ISBN: (纸本)9780769545028

Multi-core processors are becoming the dominant choice due to energy and thermal considerations, which also applies to embedded and real-time systems. While fixed-priority scheduling with task-splitting in real-time systems are widely applied, current approaches have not taken into consideration energy-aware aspects such as dynamic voltage/frequency scheduling (DVS). In this paper, we propose two strategies to apply DVS to fixed-priority scheduling algorithms with task-splitting for periodic real-time tasks on multi-core processors. We first propose a strategy that does traditional DVS for each processor after scheduling (post-DVS), which ensures all tasks meet the timing requirements on synchronization. We then propose a new strategy, which determines the frequency of each task before scheduling (pre-DVS) according to the total utilization of task-set and number of cores available, so that the system could take full advantage of all the cores. The combination of frequency pre-allocation and task-splitting makes it possible to maximize energy savings with DVS. We perform a series of simulations to compare the performance of each algorithm with two state-of-the-art scheduling algorithms with task-splitting. Simulation results show that the pre-DVS algorithm we proposed has performed satisfactorily on both schedulability and energy consumption in comparison to the previous approaches.

关键词： Real-time systems multi-core scheduling dynamic voltage scaling (DVS) energy optimization

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