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检索条件"主题词=Optimization Algorithm"

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Two Local Search Components that Move Along the Axes for Memetic Computing Frameworks

Two Local Search Components that Move Along the Axes for Mem...

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2014 IEEE Symposium on Foundations of Computational Intelligence (FOCI)

作者： Neri, Ferrante Khan, Noel De Montfort Univ Ctr Computat Intelligence Sch Comp Sci & Informat Gateway Leicester LE1 9B1L Leics England

ISBN: (纸本)9781479944910

Within memetic computing frameworks, the structure as well as a correct choice of memes are important elements that drive successful optimization algorithms. This paper studies variations of a promising yet simple search operator, the S algorithm, which can easily be integrated within a memetic framework to improve candidate solutions. S is a single-solution optimizer that iteratively perturbs variables and conditionally evaluates solutions along the axes. The first S variant, namely S2, unconditionally evaluates solutions in both directions while S3 maintains D uncorrelated step sizes that are either expanded in the direction of improving fitness or else redirected and contracted. Numerical results from the CEC2010 and CEC2014 benchmarks show that the variants outperform S in terms of the number of function evaluations for a given fitness value and, further, that S3 outperforms S in terms of final fitness against a wide range of problems and dimensionality.

关键词： evolutionary computation iterative methods optimisation search problems CEC2010 benchmark CEC2014 benchmark S algorithm conditional evaluation function evaluation iterative variable perturbation local search components memetic computing frameworks optimization algorithm search operator single-solution optimizer algorithm design and analysis Benchmark testing Correlation Market research Memetics optimization Sociology Function evaluation algorithm design and analysis Benchmark testing optimization algorithms tabu search market research Sociology evolutionary algorithm iterative methods axe Axis, Cervical Vertebra Sulfur Frameworks

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THE ANALYSIS OF THE RECESSION HYDROGRAPH'S LIMBS ON THE CHOSEN WATERSHED IN THE CZECH REPUBLIC 14

THE ANALYSIS OF THE RECESSION HYDROGRAPH'S LIMBS ON THE CHOS...

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14th International Multidisciplinary Scientific Geoconference (SGEM)

作者： Tereza, Frabsova Petr, Maca Pavel, Pech Czech Univ Life Sci Prague Fac Environm Sci Prague Czech Republic

ISBN: (纸本)9786197105131

The analysis of the recession hydrograph's limbs is based on the evaluation of the recession characteristics estimated from the runoff hydrograph on the selected catchment in the Czech Republic. Within this contribution the following constitutional storage discharge relationships of single accumulation space were identified: the linear, the nonlinear and the exponential reservoir. The recession limbs analysis consists of two parts. The first part explores the parameter estimation using the local optimization algorithm based on nonlinear least squares minimization, it was applied for the identification of power relationship of nonlinear reservoir. In the second part of the analysis the parameters of studied constitutive relationships are estimated using global optimization algorithm based on the Shuffled Complex Differential Evolution (SCDE). The main result of calibration is the finding that the baseflow response of basin corresponds more to the response of nonlinear reservoir on tested set of watershed.

关键词： baseflow recession limb constitutional relationship models of reservoir optimization algorithm

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Chosen numerical algorithms for interval finite element analysis

Chosen numerical algorithms for interval finite element anal...

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6th Conference on Modelling of Mechanical and Mechatronic Systems (MMaMS)

作者： Saga, Milan Vasko, Milan Pechac, Peter Univ Zilina Fac Mech Engn Dept Appl Mech Univ 1 Zilina 01026 Slovakia

Our paper presents chosen computational algorithms for solution of finite element models with structural uncertainties. An application of the chosen approaches will be presented - the first one, a simple combination of only inf-values or only sup-values;the second one presents full combination of all inf-sup values;the third one uses the optimizing process as a tool for finding out an inf-sup solution and last one is the Monte Carlo method as a comparison tool. (C) 2014 Published by Elsevier Ltd.

关键词： uncertain mechanical parameters Monte Carlo method interval arithmetic optimization algorithm

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Nonnegative Matrix Factorization for Document Clustering: A Survey

Nonnegative Matrix Factorization for Document Clustering: A ...

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13th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Hosseini-Asl, Ehsan Zurada, Jacek M. Univ Louisville Dept Elect & Comp Engn Louisville KY 40292 USA

ISBN: (纸本)9783319071756;9783319071763

Nonnegative Matrix Factorization (NMF) is a popular dimension reduction technique of clustering by extracting latent features from high-dimensional data and is widely used for text mining. Several optimization algorithms have been developed for NMF with different cost functions. In this paper we apply several methods of NMF that have been developed for data analysis. These methods vary in using different cost function for matrix factorization and different optimization algorithms for minimizing the cost function. Reuters Document Corpus is used for evaluating the performance of each method. The methods are compared with respect to their accuracy, entropy, purity and computational complexity and residual mean square root error. The most efficient methods in terms of each performance measure are also recognized.

关键词： Nonnegative Matrix Factorization Document clustering optimization algorithm

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ON THE IMPORTANCE OF OPTIMIZING IN SCHEDULING: THE PHOTOLITHOGRAPHY WORKSTATION

ON THE IMPORTANCE OF OPTIMIZING IN SCHEDULING: THE PHOTOLITH...

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Winter Simulation Conference

作者： Bitar, Abdoul Dauzere-Peres, Stephane Yugma, Claude Dept. of Manuf. Sci. & Logistics Ecole des Mines de St.-Etienne Gardanne France

ISBN: (纸本)9781479974863

This paper analyzes the impact of scheduling decisions on the capacity of a semiconductor manufacturing workstation. The studywas conducted on real industrial data of a well-known bottleneckworkstation, namely photolithography, which includes various complex constraints. The results of our numerical experiments show the importance of an effective optimization algorithm and how it impacts capacity, i.e. the cycle times of lots and thus the ability to schedule more lots. Additional computational results illustrate that, when the problem complexity is reduced by ignoring setup times, the impact of determining optimized schedules is also reduced.

关键词： optimisation photolithography semiconductor industry optimization algorithm photolithography workstation scheduling decisions semiconductor manufacturing workstation Genetic algorithms Job shop scheduling Lithography Scheduling algorithms Workstations

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Evolutionary Clustering Detection of Similarity in Neuronal Spike Patterns

Evolutionary Clustering Detection of Similarity in Neuronal ...

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11th International Symposium on Neural Networks (ISNN)

作者： Lu, Hu Liu, Zhe Song, Yuqing Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9783319124360;9783319124353

The key to interpreting multi-electrode recorded neuronal spike trains are the firing patterns hidden in a population of neurons. Here, we present a new firing pattern detection method based on community structure partitioning method, in which we apply the genetic evolutionary algorithm to maximize modularity function Q. We propose a new genotype encoding method to represent the functional connections between neurons. Independent of prior ` knowledge,' this method automatically finds the number and type of firing patterns in neuronal populations, an advantage over current leading methods.

关键词： optimization algorithm Modularity function Spike trains Firing patterns

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Reliability assesment in the design of interleaved converters under multi-physical constraints

Reliability assesment in the design of interleaved converter...

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IEEE 23rd International Symposium on Industrial Electronics (ISIE)

作者： Bendali, Mahraz Larouci, Cherif Azib, Toufik Marchand, Claude Coquery, Gerard ESTACA Engineer Sch CERIE Levallois Perret France Univ Paris Sud LGEP Gif Sur Yvette France IFSTTAR Versailles France

ISBN: (纸本)9781479923991

This paper presents the integration of the reliability assessment in a pre-design approach of interleaved converters for embedded automotive applications. This approach is based on a multi-physic optimization to pre-size the entire converter and its components. The design constraints are progressively integrated, in addition the reliability aspect of power components is considered in the early steps of the design. The proposed method is applied to an Interleaved Buck Converter IBC. It allows to pre-size converter determining the optimal number of cells under multi-physics constraints such as electric, efficiency, thermal, volume and in particularly the reliability, which is considered in same level of pre-design to eliminate all risk of feasibility. This paper describes the reliability assessment approach of the converter using the FIDES methodology for components reliability. Therefore, this approach takes account of mission profile associated with operating conditions to assess the lifetime of power converter.

关键词： optimization algorithm FIDES Reliability Interleaved buck converter design methodology

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Optimal Placement and Sizing of Multi Distributed Generations with Renewable Bus Available limits using Shuffled Bat algorithm 27

Optimal Placement and Sizing of Multi Distributed Generation...

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IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Yammani, Chandrasekhar Maheswarapu, Sydulu Matam, Sailaja Kumari IEEE India

ISBN: (纸本)9781479930999

In this paper a new optimization algorithm is proposed for optimal planning of the Distributed generation (DG's) with renewable bus available limit constraint. Distribution system objectives considered for optimization are Active and reactive power losses minimization, bus voltage profile improvement, and line flow capacity limits. Power system modeled Distributed generations such as wind, solar and fuel cell and some artificial models like micro turbines are used to study the proposed algorithm. To optimize the objective function with voltage limits and renewable DG bus available limit constraints, Shuffled Bat algorithm (ShBAT) is proposed and compared with Genetic algorithm (GA) and Bat algorithm (Bat). 84-bus distribution system testing with proposed algorithm is presented with results.

关键词： Distributed Generation(DG) Distribution system loading Loss minimization optimization algorithm Shuffled Bat algorithm

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Comparative Study of Transformer Topologies for Distributed IPT Systems

Comparative Study of Transformer Topologies for Distributed ...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Lanaras, Evangelos Prasanth, Venugopal Bauer, Pavol Delft Univ Technol NL-2600 AA Delft Netherlands

ISBN: (纸本)9781479956159

Distributed inductive power transfer (IPT) systems address the range restrictions of electric vehicles (EVs), charging the battery on-road through a loosely coupled transformer. Comparing different primary and secondary coil topologies is the main objective of this paper. Variations including single and multiphase layouts are analyzed by laboratory experimentation and finite element simulations. A system parameter optimization algorithm is introduced, utilizing sensitivity analysis techniques and equivalent circuit representation. Interphase power circulation in multiphase system primaries is addressed by a terminal correction setup, minimizing the interphase mutual inductance. The optimized designs are compared in terms of power and efficiency under alignment variations.

关键词： Inductive power transfer interphase mutual inductance optimization algorithm quadrature pick-up

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Power Transformer Fault Classification by Combining Genetic Reduction with Optimized Multilayer Support Vector Machine

Power Transformer Fault Classification by Combining Genetic ...

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IEEE Innovative Smart Grid Technologies - Asia

作者： H.Z. Li S.X. Chen T. Qian W.H. Tang Q.H. Wu Foshan Power Supply Bureau of Guangdong Province No. 1 Fenjiang South Rd. Chancheng District Foshan 528000 China School of Electric Power Engineering South China University of Technology Guangzhou 510641 China

ISBN: (纸本)9781509012398

This paper presents a novel fault diagnosis model for oil-immersed power transformers based on dissolved gas analysis. The model is rooted on the theories of rough set and support vector machine. A fitness function based on attribute dependence is developed to identify fault features to improve classification accuracy of transformer fault samples by using Genetic algorithm. To get improved classification performance, grid search, genetic algorithm and particle swarm optimization are applied to search parameters of support vector machine. Compared with modified Rogers and back propagation neural network, the superiority of the established model is verified.

关键词： genetic reduction multilayer support vector machine optimization algorithm rough set transformer fault diagnosis

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