Search Results - (( square optimization method algorithm ) OR ( data optimization based algorithm ))
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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Short term traffic forecasting based on hybrid of firefly algorithm and least squares support vector machine
Published 2015“…The goal of an active traffic management is to manage congestion based on current and predicted traffic conditions.This can be achieved by utilizing traffic historical data to forecast the traffic flow which later supports travellers for a better journey planning.In this study, a new method that integrates Firefly algorithm (FA) with Least Squares Support Vector Machine (LSSVM) is proposed for short term traffic speed forecasting, which is later termed as FA-LSSVM.In particular, the Firefly algorithm which has the advantage in global search is used to optimize the hyper-parameters of LSSVM for efficient data training. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2018“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks
Published 2024“…Secondly, this thesis invents the new bio-inspired Gooseneck Barnacle Optimization Algorithm (GBO), drawing inspiration from gooseneck barnacle mating behaviors, to address the limitations of the original BMO and its variants, aiming for more realistic and robust optimization. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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System identification using Extended Kalman Filter
Published 2017“…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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Complex-valued nonlinear adaptive filters for noncircular signals
Published 2017“…The augmented CNGD has shown low Means Square Error (MSE) capabilities and have optimal performance than the conventional algorithm. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…The proposed method achieved superior forecasting accuracy compared to benchmark algorithms including standard teaching-learning-based optimization with extreme learning machine, manta rays foraging optimization with extreme learning machine, moth flame optimization with extreme learning machine, ant colony optimization with extreme learning machine and salp swarm algorithm with extreme learning machine. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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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“…PSO is a swarm-based search algorithm perform a stochastic search to explore the search space. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
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Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
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