Search Results - (( model evaluation bee algorithm ) OR ( parameters estimation system algorithm ))
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Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search
Published 2019“…In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved. …”
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Book Chapter -
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. …”
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Estimation in spot welding parameters using genetic algorithm
Published 2007“…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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Thesis -
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Group method of data handling with artificial bee colony in combining forecasts
Published 2018“…The weights for each individual model are calculated using ABC algorithm. In order to evaluate the proposed model, this study tested the proposed model on the International Airline Passengers data, and the performances are calculated using mean square error (MSE), mean average error (MAE) and mean average percentage error (MAPE). …”
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A new metaphor-less algorithms for the photovoltaic cell parameter estimation
Published 2023“…Multiobjective optimization; Parameter estimation; Photoelectrochemical cells; Photovoltaic cells; Solar power generation; Cell parameter; Estimated parameter; Local minimums; Optimization algorithms; Pre-mature convergences; Solar cell parameters; Solar photovoltaic system; Solar PVs; Solar cells…”
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Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network
Published 2023“…This thesis will be presented by implementing simulated, and benchmark data sets with multiple performance evaluation metrics. Based on the findings, the proposed model outperforms other models.…”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…In addition, four types of intrusion detection evaluation datasets were applied to evaluate the proposed model in comparison to the others. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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Conference or Workshop Item -
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…Both the model order and the parameters of the system are estimated simultaneously to attain the best mathematical model of a system. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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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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Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway
Published 2023“…Most of the estimated kinetic parameter values obtained from the proposed algorithm are the closest to the experimental data.…”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The estimation of SL values was achieved using inputs of previous SL and streamflow values provided to the models. Various statistical metrics were used to evaluate the accuracy of the established hybrid and stand-alone models. …”
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Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…Modelling based on input and output data is known as system identification. One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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