Journal ArticleDOI
Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm
Chaoshun Li,Jianzhong Zhou +1 more
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TLDR
The improved gravitational search algorithm (IGSA), together with genetic algorithm, particle swarm optimization and GSA, is employed in parameter identification of HTGS and is shown to locate more precise parameter values than the compared methods with higher efficiency.About:
This article is published in Energy Conversion and Management.The article was published on 2011-01-01. It has received 256 citations till now. The article focuses on the topics: Meta-optimization & Multi-swarm optimization.read more
Citations
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A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms
Pinar Civicioglu,Erkan Beşdok +1 more
TL;DR: Empirical results reveal that the problem solving success of the CK algorithm is very close to the DE algorithm and the run-time complexity and the required function-evaluation number for acquiring global minimizer by theDE algorithm is generally smaller than the comparison algorithms.
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A survey on new generation metaheuristic algorithms
TL;DR: In this survey, fourteen new and outstanding metaheuristics that have been introduced for the last twenty years other than the classical ones such as genetic, particle swarm, and tabu search are distinguished.
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Optimal power flow using gravitational search algorithm
TL;DR: Simulation results obtained from the proposed GSA approach indicate that GSA provides effective and robust high-quality solution for the OPF problem.
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Combined economic and emission dispatch solution using gravitational search algorithm
TL;DR: The bi-objective optimization problem is converted into a single objective function using a price penalty factor in order to solve the CEED problem with the Gravitational Search Algorithm.
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Optimal reactive power dispatch using a gravitational search algorithm
TL;DR: In this article, the authors presented a gravitational search algorithm (GSA) for reactive power dispatch (RPD) problem, which is an optimisation problem that decreases grid congestion with one or more objective of minimising the active power loss for a fixed economic power schedule.
References
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Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
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Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
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GSA: A Gravitational Search Algorithm
TL;DR: A new optimization algorithm based on the law of gravity and mass interactions is introduced and the obtained results confirm the high performance of the proposed method in solving various nonlinear functions.
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Genetic algorithms and their applications
TL;DR: The genetic algorithm is introduced as an emerging optimization algorithm for signal processing and a number of applications, such as IIR adaptive filtering, time delay estimation, active noise control, and speech processing, that are being successfully implemented are described.