Search Results - (( data optimization max algorithm ) OR ( parameter optimization model algorithm ))
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Improving neural networks training using experiment design approach
Published 2005“…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches
Published 2015“…The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review
Published 2024“…This paper presents a review on algorithm development and crop water modelling with a focus on optimizing significant parameters related to crop factors, soil factors, and weather factors. …”
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Maximum 2-satisfiability in radial basis function neural network
Published 2020“…In this study, the effectiveness of RBFNN-MAX2SAT can be estimated by evaluating the proposed models with testing data sets. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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A new metaphor-less algorithms for the photovoltaic cell parameter estimation
Published 2023Article -
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction
Published 2023“…Article; case study; genetic algorithm; mathematical computing; process optimization; sensitivity analysis; solar radiation; statistical model; statistical parameters; support vector machine; algorithm; forecasting; human; humidity; regression analysis; solar energy; sunlight; turkey (bird); wind; Algorithms; Forecasting; Humans; Humidity; Regression Analysis; Solar Energy; Sunlight; Support Vector Machine; Turkey; Wind…”
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Parameter identification of solar cells using improved Archimedes Optimization Algorithm
Published 2023“…The parameters of solar cells for five PV models are identified using an Improved Archimedes Optimization Algorithm (IAOA) in this paper. …”
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Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm
Published 2020“…Cuckoo search algorithm is used to optimize the parameters in phenomenological Bouc-Wen model. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Hence, the model of the plant was represented by the transfer function from the identified parameters obtained from the optimization process. …”
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Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. …”
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Proceeding Paper -
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025Subjects:Article -
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences
Published 2018“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference
Published 2018“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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