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检索条件"主题词=EVOLUTIONARY PROGRAMMING"

共 651 条记录，以下是511-520 订阅

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Footstep Planning Based on Univector Field Method for Humanoid Robot

Footstep Planning Based on Univector Field Method for Humano...

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12th International FIRA RoboWorld Congress

作者： Hong, Youngdae Kim, Jong-Hwan Korea Adv Inst Sci & Technol Dept Elect Engn & Comp Sci Taejon 305701 South Korea

ISBN: (纸本)9783642039829

This paper proposes a footstep planning algorithm based on univector field method optimized by evolutionary programming for humanoid robot to arrive at a target point in a dynamic environment. The univector field method is employed to determine the moving direction of the humanoid robot at every footstep. Modifiable walking pattern generator, extending the conventional 3D-LIPM method by allowing the ZMP variation while in single support phase, is utilized to generate every joint trajectory of a robot satisfying the planned footstep. The proposed algorithm enables the humanoid robot not only to avoid either static or moving obstacles but also step over static obstacles. The performance of the proposed algorithm is demonstrated by computer simulations using a modeled small-sized humanoid robot HanSaRam (HSR)-VIII.

关键词： Footstep planning univector field method evolutionary programming humanoid robot modifiable walking pattern generator

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Stochastic optimization techniques for economic dispatch with combined cycle units

Stochastic optimization techniques for economic dispatch wit...

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9th International Conference on Probabilistic Methods Applied to Power Systems

作者： Gao, F. Sheble, G. B. Iowa State Univ Dept Elect & Comp Engn Ames IA 50010 USA

ISBN: (纸本)9789171785855

Electricity industries worldwide are undergoing a period of profound upheaval. Conventional vertically integrated mechanism is replaced by a competitive market environment. Generation companies have incentives to produce more electricity at lower cost by applying novel technology: Combined Cycle, Integrated Gasification Combined Cycle, Fuel Switching/Blending, and Dual Boiler etc. Economic dispatch becomes a non-convex optimization problem, which is difficult, even impossible to solve by conventional methods. Genetic Algorithm, evolutionary programming, and Particle Swarm share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve non-convex optimization problem. This paper implements GA, EP, PS algorithms for economic dispatch including combined cycle units, and makes a comparison with classical Mixed Integer Linear programming. The trajectory and searching path of each stochastic optimization technique are shown and compared. The numerical results show that the stochastic optimization techniques are capable of providing approximate global optimal solution for non-convex optimization problem.

关键词： combined cycle units evolutionary programming genetic algorithm non-convex optimization particle swarm stochastic optimization

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Using Interactive evolutionary Computation (IEC) with Validated Surrogate Fitness Functions for Redistricting 12

Using Interactive Evolutionary Computation (IEC) with Valida...

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： Chou, Christine Kimbrough, Steven O. Sullivan-Fedock, John Woodard, C. Jason Murphy, Frederic H. Natl Dong Hwa Univ Dept Int Business Hualien 97401 Taiwan

ISBN: (纸本)9781450311779

We describe a novel use of evolutionary computation to discover good districting plans for the Philadelphia City Council. We discovered 116 distinct, high quality, legally valid plans. These constitute a rich resource for stakeholders to base deliberation. This raises the issue of how to deal with large numbers of plans, especially with the aim of avoiding gerrymandering and promoting fairness. Interactive evolutionary Computation (IEC) is a natural approach here, if practicable. The paper proposes development of Validated Surrogate Fitness (VSF) functions as a workable and generalizable form of IEC.

关键词： interactive evolutionary computation evolutionary programming districting compactness

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A Wide Band Wire Antenna for WLAN and Wi-Fi Applications

A Wide Band Wire Antenna for WLAN and Wi-Fi Applications

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IEEE EUROCON Conference

作者： Casula, Giovanni Andrea Mazzarella, Giuseppe Montisci, Giorgio Fanti, Alessandro Maxia, Paolo Univ Cagliari Dipartimento Ingn Elettr & Elettron I-09123 Cagliari Italy

ISBN: (纸本)9781467322324;9781467322300

This paper presents a wire antenna for multi-band WLAN application, designed using the Structure-Based evolutionary programming, and having a very simple geometry. The antenna has been analysed with NEC-2 during the evolutionary process, and the outcome of the procedure shows a very good performance, with a -10dB bandwidth that covers the required frequencies for multi-band WLAN applications (2.4/5.2/5.8 GHz) and beyond, and an end-fire gain greater than 11 dB.

关键词： Wire Antennas evolutionary programming Wide Band Antennas

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Artificial Intelligence Technique Based Reactive Power Planning Incorporating FACTS Controllers in Real Time Power Transmission System 2

Artificial Intelligence Technique Based Reactive Power Plann...

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IEEE 2nd International Conference on Electrical Energy Systems (ICEES)

作者： Vadivelu, Kallipatti Ramsamy Marutheswar, G. Venkata Annamacharya Inst Technol & Sci Elect & Elect Engn Tirupati Andhra Pradesh India SV Univ Coll Engn Elect & Elect Engn Tirupati Andhra Pradesh India

ISBN: (纸本)9781479937394

Reactive Power Planning is a major concern in the operation and control of power systems This paper compares the effectiveness of evolutionary programming (EP) and Differential Evolution to solve Reactive Power Planning (RPP) problem incorporating FACTS Controllers like Static VAR Compensator (SVC), Thyristor Controlled Series Capacitor (TCSC) and Unified power flow controller (UPFC) considering voltage stability. With help of Fast Voltage Stability Index (FVSI), the critical lines and buses are identified to install the FACTS controllers. The optimal settings of the control variables of the generator voltages, transformer tap settings and allocation and parameter settings of the SVC,TCSC,UPFC are considered for reactive power planning. The test and Validation of the proposed algorithm are conducted on IEEE 30 bus system and 72-bus Indian *** results shows that the UPFC gives better results than SVC and TCSC and the FACTS controllers reduce the system losses.

关键词： FACTS Devices SVC TCSC UPFC Reactive power planning Fast Voltage Stability Index evolutionary programming Differential Evolution

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An evolutionary fuzzy neural network approach for Short-Term Electric Power Load Forecasting

An evolutionary fuzzy neural network approach for Short-Term...

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General Meeting of the Power-Engineering-Society

作者： Liao, Gwo-Ching Fortune Inst Technol Dept Elect Engn Kaohsiung Taiwan

ISBN: (纸本)9781424404926

A Hybrid evolutionary programming and Fuzzy Neural Network (HEFNN) for load forecasting is presented in this paper. A Fuzzy Hyper-Rectangular Composite Neural Networks (FHRCNNs) was used for the initial load forecasting. evolutionary programming (EP) was then used to find the optimal solution for the parameters of FHRCNNs (including parameters such as synaptic weights, biases, membership functions, sensitivity factor in membership functions and adjustable synaptic weights). The EP generates a set of feasible solution parameters The EP has good global optimal search capabilities. The HEFNN was used to see if it could improve the solution quality and reduce the load forecasting error.

关键词： electric load forecasting evolutionary programming fuzzy neural network

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evolutionary Computation: A Unified Approach 12

Evolutionary Computation: A Unified Approach

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14th International Conference on Genetic and evolutionary Computation Conference (GECCO)

作者： De Jong, Kenneth George Mason Univ Dept Comp Sci Fairfax VA 22030 USA

ISBN: (纸本)9781450311786

The field of evolutionary Computation has experienced tremendous growth over the past 25 years, resulting in a wide variety of evolutionary algorithms and applications. The result poses an interesting dilemma for many practitioners in the sense that, with such a wide variety of algorithms and approaches, it is often hard to se the relationships between them, assess strengths and weaknesses, and make good choices for new application areas. This tutorial is intended to give an overview of a general EC framework that can help compare and contrast approaches, encourages crossbreeding, and facilitates intelligent design choices. The use of this framework is then illustrated by showing how traditional EAs can be compared and contrasted with it, and how new EAs can be effectively designed using it. Finally, the framework is used to identify some important open issues that need further research.

关键词： evolutionary programming evolution strategies evolutionary algorithms genetic programming genetic algorithms

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Comparison of Intelligent Techniques to Solve Economic Load Dispatch Problem with Line Flow Constraints

Comparison of Intelligent Techniques to Solve Economic Load ...

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IEEE International Advance Computing Conference

作者： Karthikeyan, S. Prabhakar Palanisamy, K. Varghese, L. Jacob Raglend, I. Jacob Kothari, D. P. VIT Univ Sch Elect Sci Vellore 632014 Tamil Nadu India Christian Coll Engn & Technol Oddanchatram Tamil Nadu India VIT Univ Vellore 632014 Tamil Nadu India

ISBN: (纸本)9781424429271

A comparative analysis using different intelligent techniques has been carried out for the Economic Load Dispatch (ELD) problem considering line flow constraints for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of this paper is to minimize the total production cost of the thermal power generation. Economic Load Dispatch (ELD) has been applied to obtain optimal fuel cost. Optimal Power Flow has been carried out to obtain ELD solutions with minimum operating cost satisfying both unit and network constraints. In this paper, various intelligent techniques such as Genetic Algorithm (GA), evolutionary programming (EP), Particle Swarm Optimization (PSO), and Differential Evolution (DE) have been applied to obtain ELD solutions. The proposed algorithm has been tested on two sample systems viz IEEE 30 bus system and a 15 unit system. The results obtained by the various intelligent techniques are compared. The solutions obtained are quite encouraging and useful in the economic environment. The algorithm and simulation are carried out using Matlab software.

关键词： Economic Load Dispatch Genetic Algorithm evolutionary programming Particle Swarm Optimization Differential Evolution

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Multiuser detection using the particle swarm optimization algorithm

Multiuser detection using the particle swarm optimization al...

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International Symposium on Communications and Information Technologies (ISCIT2005)

作者： Liu, C Xiao, Y Beijing Jiaotong Univ Inst Informat Sci Beijing 100044 Peoples R China

ISBN: (纸本)0780395387

Genetic Algorithm (GA) has proven to be a useful method of optimization for multidimensional engineering problems. A new method named Particle Swarm Optimization (PSO) has been proposed by Kennedy and Eberhart and it is similar in some ways to GA or evolutionary Programmmig (EP). In this paper, we apply PSO to solve the Multiuser Detection (MUD) problems in the DS-CDMA system, which reduces the computational complexity by providing faster convergence. The simulation results show that the proposed detections benefit greatly from the PSO and have significant performance improvements over Conventional Detector (CD) and previous multiuser detectors based on GA and EP in terms of bit-error-rate and convergence rate.

关键词： genetic algorithm evolutionary programming multiuser detection particle swarm optimization

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Application of evolutionary techniques to short-term optimization of hydrothermal systems

Application of evolutionary techniques to short-term optimiz...

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International Conference on Power System Technology (POWERCON 2000)

作者： Manzanedo, F Castro, JL Pérez-Donsión, M Univ Vigo ETSII Vigo 36200 Spain

ISBN: (纸本)0780363388

This paper presents the implementation of evolutionary techniques for solving short-term optimization problems of hydrothermal power systems where a complete model for the hydroplants is considered. Beyond the usual water conservation equations and bounds on variables, this formulation can handle some other important aspects of hydro plants and reservoirs that are rarely taken into account. Environmental and ramping costs of thermal units and transmission losses are also included in this formulation. The optimization process consists of a simulation of both the hydraulic and the thermal subsystems to obtain feasible (but no optimal) solutions, and the application of evolutionary methods to improve the global profit of the system gradually. The algorithms are applied to a real case with several coupled hydroplants and their results are compared with the ones obtained by other classical optimization methods to show the capacity of these methods to find global or near-global optimum solutions.

关键词： energy management hydroelectric power generation power plants genetic algorithms evolutionary programming optimization methods

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