Search Results - (( evolution optimization model algorithm ) OR ( parameter simulation model algorithm ))
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Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion 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“…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso
Published 2023“…In this study, an Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm that can estimate the values of small-scale kinetic parameters is described and applied to E. coli’s main metabolic network as a model system. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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Thesis -
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A comparative study for parameter selection in online auctions
Published 2009“…Due to the complex and dynamic nature of the online auction, one of the strategies employed is using genetic algorithm to discover the best strategy. Hence, this work attempts to improve an existing bidding strategy by taking into accounts the evolution of various model of generic algorithm in optimizing the parameter of the bidding strategies. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…To show the effectiveness of EMA-DL, comparison studies were conducted among other metaheuristic optimizers that were also used to optimize the DL parameters viz, Particles Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) as well as the Adaptive Moment Estimation (ADAM). …”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…Additionally, the spiral dynamics algorithm, which draws on principles from complex adaptive systems and human values, provides a framework for modelling system evolution. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement
Published 2020“…For this study, design of proportional integral derivative (PID) PSS (PIDPSS) is proposed for damping oscillations and improve angular stability in single machine infinite bus (SMIB) power system modeled and simulated in MATLAB/SIMULINK. A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution
Published 2012“…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…Specifically, the downlink frequency domain scheduler will reconfigure the criteria priorities such that the EE is maximized as long as the QoS is guaranteed.On the other hand, the partial feedback algorithm will search for the threshold value that minimizes the uplink overhead given that the QoS is achieved at the downlink.Otherwise, optimizing QoS parameters will be targeted at the cost of other system parameters. …”
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Numerical simulation and experimental verification on distortions induced by wire-arc additive manufacturing components and costing analysis / Keval Priapratama Prajadhiana
Published 2024“…The development of numerical simulation model started by the geometrical modelling followed by material modelling based on real scanned material using JMATPRO. …”
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Metaheuristic techniques in enhancing the efficiency and performance of thermo-electric cooling devices
Published 2017“…Mathematical modelling and parameter setting of TEC is combined with SA and DE to find better optimal findings. …”
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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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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…Due to the evolution of high processing microprocessors, the model predictive control (MPC) has been widely used in power electronic applications. …”
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Thesis -
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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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