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检索条件"主题词=Evolutionary Programming"

共 650 条记录，以下是581-590 订阅

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A Study of evolutionary Multiobjective Algorithms and Their Application to Knapsack and Nurse Scheduling Problems

A Study of Evolutionary Multiobjective Algorithms and Their ...

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作者： Le, Khoi Nguyen University of Nottingham

学位级别：博士

evolutionary algorithms (EAs) based on the concept of Pareto dominance seem the most suitable technique for multiobjective optimisation. In multiobjective optimisation, several criteria (usually conflicting) need to be taken into consideration simultaneously to assess a quality of a solution. Instead of finding a single solution, a set of trade-off or compromise solutions that represents a good approximation to the Pareto optimal set is often required. This thesis presents an investigation on evolutionary algorithms within the framework of multiobjective optimisation. This addresses a number of key issues in evolutionary multiobjective optimisation. Also, a new evolutionary multiobjective (EMO) algorithm is proposed. Firstly, this new EMO algorithm is applied to solve the multiple 0/1 knapsack problem (a wellknown benchmark multiobjective combinatorial optimisation problem) producing competitive results when compared to other state-of-the-art MOEAs. Secondly, this thesis also investigates the application of general EMO algorithms to solve real-world nurse scheduling problems. One of the challenges in solving real-world nurse scheduling problems is that these problems are highly constrained and specific-problem heuristics are normally required to handle these constraints. These heuristics have considerable influence on the search which could override the effect that general EMO algorithms could have in the solution process when applied to this type of problems. This thesis outlines a proposal for a general approach to model the nurse scheduling problems without the requirement of problem-specific heuristics so that general EMO algorithms could be applied. This would also help to assess the problems and the performance of general EMO algorithms more fairly.

关键词： evolutionary programming evolutionary computation computer algorithms knapsack problem nurse scheduling

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Load Management for Voltage Stability Control in Multi-Area Power System 6

Load Management for Voltage Stability Control in Multi-Area ...

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6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

作者： Mustaffa, Sharifah Azma Syed Musirin, Ismail Othman, Muhammad Murthada Salimin, Rahmatul Hidayah Univ Tenaga Nas Coll Engn Kajang Selangor Malaysia Univ Teknol MARA Fac Elect Engn Shah Alam Selangor Malaysia

ISBN: (纸本)9781509011780

Voltage stability is one of the important issues in the existing power system network and in this paper presents the reactive power load management for voltage stability control in multi-area power system. evolutionary programming (EP) as optimization technique was employed in order to manage the load with the aim to control the voltage stability. Pre-developed Fast Voltage Stability Index (FVSI) was utilized as an instrument for voltage security assessment. Single-load and multi-load increment were performed on several loading conditions to obtain maximum reactive power loading with FVSI range from 0 to 0.95 p.u. The proposed EP optimization technique managed to outperform the traditional voltage stability assessment (VSA) approach in terms of achieving accurate results.

关键词： Fast Voltage Stability Index (FVSI) evolutionary programming Reactive Power Loading

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A new profit-based unit commitment considering power and reserve generating

A new profit-based unit commitment considering power and res...

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Winter Meeting of the IEEE-Power-Engineering-Society

作者： Attaviriyanupap, P Kita, H Tanaka, E Hasegawa, J Hokkaido Univ Grad Sch Engn Div Syst & Informat Engn Sapporo Hokkaido Japan

ISBN: (纸本)0780373227

Because of the revolution of power system structure nowadays, operation and control of generating unit must be modified. Energy price becomes an important parameter to make a decision in this restructured system. Unit commitment (UC) in such a competitive environment is not the same as the traditional one anymore. The objective of UC is not to minimize production cost as before but to find the solution that produces a maximum profit for generation company (GENCO). This paper presents a new profit-based UC formulation under competitive environment considering both power and reserve generation. A hybrid method between Lagrange Relaxation (LR) and evolutionary programming (EP) is applied to solve this new UC problem. The proposed approach is applied to a test system. Simulation results are compared with those obtained from traditional UC.

关键词： competitive environment deregulated power system evolutionary programming Lagrange Relaxation reserve price restructured system spot price unit commitment

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Particle swarms for feedforward neural network training

Particle swarms for feedforward neural network training

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International Joint Conference on Neural Networks (IJCNN 02)

作者： Mendes, R Cortez, P Rocha, M Neves, J Univ Minho Dept Informat P-4719 Braga Portugal

ISBN: (纸本)0780372786

Particle Swarm. is a novel optimization paradigm for real-valued functions, based on the social dynamics of group interaction. In this work, it is proposed its application to the training of Neural Networks. Comparative tests were carried out, for classification and regression tasks, being the results compared with other approaches.

关键词： evolutionary programming Feedforward Neural Networks gradient-based algorithms Particle Swarm Optimization

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Optimal Design of Toraldo Super Resolving Filters

Optimal Design of Toraldo Super Resolving Filters

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Conference on Novel Optical Systems Design and Optimization XIII

作者： Hazra, L. N. Reza, N. Univ Calcutta Dept Appl Opt & Photon Kolkata 700009 W Bengal India

ISBN: (纸本)9780819482839

Pupil plane filtering provides a convenient technique for modifying the point spread function. Such modifications are used in many practical applications that require enhancement of selective frequency band in images. Also, in many new imaging paradigms, acquisition of 3D image information calls for tailoring of the 3D point spread function. This can be achieved by suitable pupil plane filtering, preferably by phase filters. By using a pupil plane filter with an array of concentric annuli, the point spread function can be tailored in a fashion such that a narrow central lobe is surrounded by neighboring lobes of low amplitude, with one or more lobes of high amplitude spaced far away from the center. In our study we intend to explore the use of phase annuli as pupil filters in tailoring of both transverse and axial resolution. Determination of such phase filters in accordance with a set of prespecified requirements for amplitude/intensity distribution around the focus constitutes a problem of nonlinear optimization. This paper reports some results of our preliminary investigations on an application of evolutionary programming in solving this problem to obtain globally or quasi-globally optimum solutions.

关键词： Superresolution High resolution imaging Pupil plane Filtering Phase Filters Global Optimization evolutionary programming Genetic Algorithm

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Cyber-Secure UAV Communications using Heuristically Inferred Stochastic Grammars and Hard Real-Time Adaptive Waveform Synthesis and Evolution 18

Cyber-Secure UAV Communications using Heuristically Inferred...

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IEEE 18th International Conference on Information Reuse and Integration (IRI)

作者： Rubin, Stuart H. Grefe, William K. Bouabana-Tebibel, Thouraya Chen, Shu-Ching Shyu, Mei-Ling Simonsen, Kenneth S. Space & Naval Warfare Syst Ctr Pacific San Diego CA 92152 USA Ecole Natl Super Informat LCSI Lab Bab Ezzouar Algeria Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA Univ Miami Dept Elect & Comp Engn Coral Gables FL 33124 USA

ISBN: (纸本)9781538615621

This paper initially describes how an inferred context-free (stochastic) grammar can be used to verify command transmissions and serve as a hedge against a successful cyber-attack. The remainder of the paper addresses a computational problem not amenable to closed-form solution;namely, the hard real-time (similar to 57 usec) synthesis of a desired waveform through the adaptive modification of a carrier wave. This effectively increases the signal to noise ratio - ensuring better UAV communications. Here, the modulation of the primary waveform is under user control and is of strictly positive amplitude. The primary waveform induces a secondary waveform having delayed leading and trailing edges and expanded rise and fall times. There is, in general, a direct relation between the period of the primary waveform and the amplitude of the secondary waveform. The relation between the primary and secondary waveforms may be characterized by trigonometric functions or even interpolating polynomials. However, response time will be minimized where the primary waveforms are discretized and stored in the form of array-based cases. The tertiary (target) wave may be any periodic trigonometric function, but is taken to be a simple sine wave without loss of generality. The task of the adaptive program is to minimize parallel to s(t) - g(t)parallel to 2, where f(t) -> g(t) and f(t) is the primary waveform at time t, g(t) is the secondary waveform at time t, and s(t) is the tertiary waveform at time t. A computationally efficient algorithm is provided for solving this task in real time. Moreover, an evolutionary program (EP) is provided for automatic case acquisition. Primary waveforms are mutated in accordance with a normal distribution.

关键词： Adaptive programming Case-Based Reasoning evolutionary programming Expectation-Driven Receiver Grammatical Inference Hard Real-Time Systems Waveform Analysis and Synthesis

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Robust Image Registration for Multiple Exposure High Dynamic Range Image Synthesis

Robust Image Registration for Multiple Exposure High Dynamic...

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Conference on Image Processing: Algorithms and Systems IX

作者： Yao, Susu ASTAR Inst Infocomm Res Singapore 138632 Singapore

ISBN: (纸本)9780819484079

Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images.

关键词： Image registration phase correlation phase congruency evolutionary programming HDR imaging

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Research and New Development of Application of the Estimation of Distribution Algorithms

Research and New Development of Application of the Estimatio...

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2nd International Conference on Information and Computing Science

作者： Wang, Dandan Jiang, Yong Li, Jianliang Nanjing Univ Sci & Technol Dept Informat & Comp Sci Nanjing 210094 Peoples R China

ISBN: (纸本)9780769536347

The Estimation of Distribution Algorithms (EDAs) is a novel class of evolutionary algorithms which is motivated by the idea of building probabilistic graphical model of promising solutions to represent linkage information between variables in chromosome. Through learning of and sampling from probabilistic graphical model, new population is generated and optimization procedure is repeated until the stopping criteria are met. In this paper, the mechanism of the Estimation of Distribution Algorithms is analyzed. Currently existing EDAs are surveyed and categorized according to the probabilistic model they used.

关键词： genetic algorithm evolutionary programming estimation of distribution algorithms

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Differential Evolution based OPF with Conventional and Non-Conventional Cost Characteristics

Differential Evolution based OPF with Conventional and Non-C...

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Joint International Conference on Power Systems Technology (POWERCON)/IEEE Power India Conference

作者： Vaisakh, K. Srinivas, L. R. Andhra Univ Dept Elect Engn Autonomous Coll Engn Visakhapatnam 530003 Andhra Pradesh India SRKR Engn Dept Elect Engn Bhimavaram 534204 AP India

ISBN: (纸本)9781424417636

An efficient evolutionary-based approach, termed as Differential Evolution (DE), is presented for the solution of Optimal Power Flow (OPF) with the continuous variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, transformer tap settings and switchable shunt devices. The differential evolution is illustrated for two case studies of IEEE-30 bus system. Both conventional and non-conventional cost characteristics are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple evolutionary, programming algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.

关键词： Conventional and non-conventional cost characteristics differential evolution evolutionary programming optimal power flow

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Turbulent Crazy Particle swarm Optimization Technique for Optimal Reactive Power Dispatch

Turbulent Crazy Particle swarm Optimization Technique for Op...

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World Congress on Nature and Biologically Inspired Computing

作者： Roy, P. K. Ghoshal, S. P. Thakur, S. S. Dr BC Roy Engn Coll Dept Elect Engn Durgapur W Bengal India Natl Inst Technol Dept Elect Engn Durgapur W Bengal India

ISBN: (纸本)9781424450534

In this paper, a new particle swarm optimization (PSO) algorithm namely Turbulent Crazy Particle swarm Optimization (TRPSO) is introduced to solve multi-constrained optimal reactive power dispatch in power system. Optimal reactive power dispatch problem is a multi-objective optimization problem that minimizes bus voltage deviations and transmission loss. The feasibility of the proposed algorithm is demonstrated for IEEE 30-bus system and it is compared to other well established population based optimization techniques like conventional PSO, general passive congregation PSO (GPAC), local passive congregation PSO (LPAC), coordinated aggregation (CA) and Interior point based OPF (IP-OPF). A comparison of simulation results indicates that the proposed algorithm can produce better solution than other optimization techniques.

关键词： Optimal reactive power Flow Particle Swarm Optimization evolutionary programming turbulence passive congregation

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