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8th IET International Conference on Power Electronics, Machines and Drives (PEMD 2016)

作者： Zheng Tan N. J. Baker Wenping Cao Electrical Power Research Group School of Electrical and Electronic Engineering Newcastle University NE1 7RU UK Newcastle University Newcastle upon Tyne Tyne and Wear GB Aston University United Kingdom

ISBN: (纸本)9781510825666

This paper presents a case study for multi-variable and multimodal design optimisation of a doubly fed induction generator (DFIG) based on surrogate-model optimisation algorithm. The DFIG's winding of stator and rotor are optimised to obtain higher efficiency for rewinding purposes. First, a Latin hypercube design is selected as the design of experiments to obtain sampling points. Then, the surrogate model is constructed using Kriging Model (KRG) method based on the Latin hypercube design. Finally, the particle swarm optimisation algorithm is applied in conjunction with the finite element method to achieve the machine design optimisation.

关键词： DFIG Kriging model Particle swarm optimisation Particle swarm optimization optimization algorithms Optimal design Finite element method electric machines double-fed induction generator Case studies Hypercube Latin

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Power Allocation for Cognitive Relay Systems

Power Allocation for Cognitive Relay Systems

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World Congress on Intelligent Control and Automation

作者： Lina. Fan Jinkuan. Wang Jing. Gao Engineer Optimization& Smart Antenna Institute Northeastern University at Qinhuangdao Qin huang dao China Northeastern University Shenyang China

ISBN: (纸本)9781467384155

In this paper, the power allocation problem for Orthogonal frequency division multiplexing (OFDM)-based relay cognitive radio systems is investigated. An optimization power allocation algorithm is developed. In the algorithm, objective function is studied and simplified. The channel capacity of secondary users is maximized while keeping the total interference introduced to primary user less than a given threshold with a specified power. Compared to the optimal algorithm and the average power allocation algorithm, the proposed algorithm is close to the optimal algorithm and has a better performance than average power allocation algorithm, and has low complexity.

关键词： Relays Resource management Cognitive radio Interference Signal processing algorithms OFDM optimization Signal processing algorithms Relay systems power splitting relay Cognitive radio management of resources Orthogonal frequency division multiplexing optimization algorithms Allocation Algorithm Channel capacity interference average power

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Optimisation and characterisation of a planar transformer with a high voltage ratio and high output voltage for plasma reactors

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IET POWER ELECTRONICS 2015年第6期8卷 929-937页

作者： Lefranc, Pierre Odic, Emmanuel Kirkpatrick, Mike J. Univ Grenoble Alpes G2Elab F-38000 Grenoble France CNRS G2Elab F-38000 Grenoble France Power Elect Team F-38402 St Martin Dheres France Supelec E3S Dept Power & Energy Syst F-91192 Gif Sur Yvette France

This study presents a new design of a planar transformer for dielectric barrier discharge (DBD). The requirements for such designs are mainly a high voltage ratio, a high voltage value at the secondary side, a specific shape for industrial applications (planar shape in this case), a low volume and a high dv/dt value at the secondary side for capacitive loads. So as to propose an efficient design tool to power electronics designers, the authors propose a virtual prototyping methodology based on an optimisation algorithm and a finite element simulation software. Towards this case study, power electronics designers can use this methodology (bi-objective optimisation algorithm) to treat new designs and especially for very innovative power converters for DBD reactors. The first objective is to pre-size the planar transformer (geometrical variables). Virtual solutions are proposed on a Pareto front: the power designer can chose the best one according to specific contexts (cost, shape, volume, efficiency etc.). In a second step, the authors propose experimental results and highlight the voltage probes modelling that must be taken into account in the case of very fast transient waveforms especially for capacitive loads such as DBD reactors.

关键词： Reactors voltage ratio Transformer power conversion unit voltage probe Designers plasma reactor secondary side design tools output voltage optimization algorithms Planar updated design High Voltage

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Relay transmit power allocation for distributed-space-time block code cognitive small cell networks

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IET COMMUNICATIONS 2015年第14期9卷 1691-1698页

作者： Ndong, Massa Fujii, Takeo Univ Electrocommun Adv Wireless Commun Res Ctr AWCC Chofu Tokyo 1828585 Japan

Small cell networks enhance spectrum efficiency by handling the indoor traffic of mobile networks on a frequency-reuse operation. Since most of the current mobile traffic happen in indoor, the authors introduce a prioritisation shift by imposing a limitation on the outage generated by the outdoor mobile system to the indoor small cells. The prioritisation shift consists of setting an outage probability threshold limitation on the macrocell system which is classically considered as a primary system. In this study, they consider downlink spectrum sharing between a system consisting of small cells and a macrocell with relays. The relays constitute a distributed-space-time block code (STBC) relaying for the outdoor system terminals. New closed-form expressions are derived to validate the proposed bit error rate (BER) function used in their optimisation algorithm considering STBC with unequal branch SNR. They propose a joint transmit antenna selection and power allocation which minimises the proposed BER. The proposed optimisation yields a dynamic selection of the relays with power control pertaining to the outdoor mobile terminal performance. The simulation results show that their proposal exhibits a better BER compared with the conventional Alamouti STBC with equal power allocation.

关键词： spectral efficiency relay optimization algorithms transmitting antennas Transmitter power primary system Outdoors space time block coding macrocells power splitting mobile networking

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Sampling approach to sparse approximation problem: determining degrees of freedom by simulated annealing

Sampling approach to sparse approximation problem: determini...

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European Signal Processing Conference

作者： Tomoyuki Obuchi Yoshiyuki Kabashima Department of Mathematical and Computing Science Tokyo Institute of Technology

ISBN: (纸本)9781509018918

The approximation of a high-dimensional vector by a small combination of column vectors selected from a fixed matrix has been actively debated in several different disciplines. In this paper, a sampling approach based on the Monte Carlo method is presented as an efficient solver for such problems. Especially, the use of simulated annealing (SA), a metaheuristic optimization algorithm, for determining degrees of freedom (the number of used columns) by cross validation is focused on and tested. Test on a synthetic model indicates that our SA-based approach can find a nearly optimal solution for the approximation problem and, when combined with the CV framework, it can optimize the generalization ability. Its utility is also confirmed by application to a real-world supernova data set.

关键词： Degree of freedom simulated annealing approximation Monte Carlo technique optimization algorithms cross-validation optimal solution column vector

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Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint 16

Adaptive Maximization of Pointwise Submodular Functions With...

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Annual Conference on Neural Information Processing Systems

作者： Nguyen Viet Cuong Huan Xu Department of Engineering University of Cambridge Stewart School of Industrial & Systems Engineering Georgia Institute of Technology

ISBN: (纸本)9781510838819

We study the worst-case adaptive optimization problem with budget constraint that is useful for modeling various practical applications in artificial intelligence and machine learning. We investigate the near-optimality of greedy algorithms for this problem with both modular and non-modular cost functions. In both cases, we prove that two simple greedy algorithms are not near-optimal but the best between them is near-optimal if the utility function satisfies pointwise submodularity and pointwise cost-sensitive submodularity respectively. This implies a combined algorithm that is near-optimal with respect to the optimal algorithm that uses half of the budget. We discuss applications of our theoretical results and also report experiments comparing the greedy algorithms on the active learning problem.

关键词： greedy algorithm Budgets Artificial Intelligence optimization algorithms Modularity

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COHERENCE REGULARIZED DICTIONARY LEARNING

COHERENCE REGULARIZED DICTIONARY LEARNING

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Mansour Nejati Shadrokh Samavi S. M. Reza Soroushmehr Kayvan Najarian ECE Department Isfahan University of Technology Iran Department of Emergency Medicine University of Michigan Ann Arbor USA

ISBN: (纸本)9781479999897

Sparse representations over redundant learned dictionaries have shown to produce high quality results in various image processing tasks. An important characteristic of a learned dictionary is the mutual coherence of dictionary that affects its generalization performance and the optimality of sparse codes generated from it. In this paper, we present a dictionary learning model equipped with coherence regularization. For this model, two novel dictionary optimization algorithms based on group-wise minimization of inter- and intra-coherence penalties are proposed. Experimental results demonstrate that the proposed algorithms improve the generalization properties and sparse approximation performance of the trained dictionary compared to several incoherent dictionary learning methods.

关键词： Dictionary learning mutual coherence sparse representation optimization sparse coding Dictionaries as Topic Sparse coding sparse representation coherence optimization algorithms

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EXPERIMENTS TO TRACK STORMS USING MODERN optimization algorithms

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Journal of Tropical Meteorology 2010年第3期16卷 280-291页

作者：李南魏鸣 Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science & Technology School of Atmospheric Physics Nanjing University of Information Science & Technology State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences

Storm identification and tracking based on weather radar data are essential to nowcasting and severe weather warning. A new two-dimensional storm identification method simultaneously seeking in two directions is proposed, and identification results are used to discuss storm tracking algorithms. Three modern optimization algorithms （simulated annealing algorithm, genetic algorithm and ant colony algorithm） are tested to match storms in successive time intervals. Preliminary results indicate that the simulated annealing algorithm and ant colony algorithm are effective and have intuitionally adjustable parameters, whereas the genetic algorithm is unsatisfaetorily constrained by the mode of genetic operations Experiments provide not only the feasibility and characteristics of storm tracking with modern optimization algorithms, but also references for studies and applications in relevant fields.

关键词： raw weather radar data storm identification and tracking optimization algorithms

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Non-invasive identification of turbo-generator parameters from actual transient network data

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第11期9卷 1129-1136页

作者： Hutchison, Greame Zahawi, Bashar Harmer, Keith Gadoue, Shady Giaouris, Damian Parsons Brinckerhoff Newcastle Upon Tyne NE4 7YQ Tyne & Wear England Khalifa Univ Dept Elect & Comp Engn Abu Dhabi 127788 U Arab Emirates Newcastle Univ Sch Elect & Elect Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England Univ Alexandria Fac Engn Dept Elect Engn Alexandria 21544 Egypt Ctr Res & Technol Hellas Chem Proc Engn Res Inst Thessaloniki 57001 Greece

Synchronous machines are the most widely used form of generators in electrical power systems. Identifying the parameters of these generators in a non-invasive way is very challenging because of the inherent non-linearity of power station performance. This study proposes a parameter identification method using a stochastic optimisation algorithm that is capable of identifying generator, exciter and turbine parameters using actual network data. An eighth order generator/turbine model is used in conjunction with the measured data to develop the objective function for optimisation. The effectiveness of the proposed method for the identification of turbo-generator parameters is demonstrated using data from a recorded network transient on a 178 MVA steam turbine generator connected to the UK's national grid.

关键词： synchronous machines network data Objective function turbogenerators power systems parameters Identification methods optimization algorithms nonlinearity

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Cyclades: Conflict-free Asynchronous Machine Learning 16

Cyclades: Conflict-free Asynchronous Machine Learning

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Annual Conference on Neural Information Processing Systems

作者： Xinghao Pan Maximilian Lam Stephen Ti Dimitris Papailiopoulos Ce Zhang Michael I. Jordan Kannan Ramchandran Chris Re Benjamin Recht Department of Electrical Engineering and Computer Science UC Berkeley Berkeley CA Department of Computer Science Stanford University Palo Alto CA Department of Electrical Engineering and Computer Science UC Berkeley Berkeley CADepartment of Statistics UC Berkeley Berkeley CA

ISBN: (纸本)9781510838819

We present Cyclades, a general framework for parallelizing stochastic optimization algorithms in a shared memory setting. Cyclades is asynchronous during model updates, and requires no memory locking mechanisms, similar to Hog-??wild!-type algorithms. Unlike HOGWILD!, Cyclades introduces no conflicts during parallel execution, and offers a black-box analysis for provable speedups across a large family of algorithms. Due to its inherent cache locality and conflict-??free nature, our multi-core implementation of Cyclades consistently outperforms Hogwild!-type algorithms on sufficiently sparse datasets, leading to up to 40% speedup gains compared to Hogwild!, and up to 5× gains over asynchronous implementations of variance reduction algorithms.

关键词： Cyclades Asynchronous parallel execution shared memory large family asynchronous machines optimization algorithms Model updating Conflict (Psychology) algorithms

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