Search Results - (( evolution optimization model algorithm ) OR ( control optimization window algorithm ))
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Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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Proceeding Paper -
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Reliably optimal PMU placement using disparity evolution-based genetic algorithm
Published 2017“…The optimization model is solved for IEEE 118 standard bus system. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…Global optimisation method includes differential evolution algorithm, which will be used in this research. …”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks
Published 2016“…Additionally, the assured service is designed for applications relying on the Transmission Control Protocol (TCP). This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution
Published 2019“…From the results obtained, the Analytical Sub-Domain Differential Evolution Algorithm (ASDEA) has better optimization technique capability compared with Analytical Sub-Domain Particle Swarm Optimization (ASPSO). …”
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Thesis -
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Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm
Published 2013“…The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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A holistic review on artificial intelligence techniques for well placement optimization problem
Published 2020“…Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. …”
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Optimization of handover algorithms in 3GPP long term evolution system
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Proceeding Paper -
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
Conference Paper -
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. …”
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QTCP: an optimized and improved congestion control algorithm of high-speed TCP networks
Published 2011“…To overcome these problems Quick Transport Control Protocol (QTCP) algorithm based on optimizations of HS-TCP slow start algorithm and Additive Increase and Multiplicative Decrease (AIMD) algorithm have been proposed. …”
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Dual optimization approach in discrete Hopfield neural network
Published 2024“…Quantitative evaluations show that the proposed model successfully enhances the optimization of both phases, ranking first compared to 10 recent algorithms for all metrics. …”
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Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking
Published 2024“…This study introduces the Vertical Farming System Multi-Robot Trajectory Planning (VFSMRTP) model. To optimize this model, we propose the Elitist Preservation Differential Evolution Grey Wolf Optimizer (EPDE-GWO), an enhanced version of the Grey Wolf Optimizer (GWO) incorporating elite preservation and differential evolution. …”
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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks
Published 2022“…The second part proposes an optimized flexible window-overlapping scheduling (OFWOS) algorithm that optimizes the offset difference ( ) between the samepriority TT windows in the adjacent nodes. …”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization
Published 2009“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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