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Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines
Published 2022-04-01“…By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. …”
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Design of efficient generalized digital fractional order differentiators using an improved whale optimization algorithm
Published 2025-07-01“…The proposed method utilizes an improved whale optimization algorithm (IWOA) to compute the optimal coefficients of IIR subfilters of the realization structure. …”
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Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation
Published 2019-01-01“…Many optimization problems have become increasingly complex, which promotes researches on the improvement of different optimization algorithms. …”
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Optimal sizing and placement of STATCOM, TCSC and UPFC using a novel hybrid genetic algorithm-improved particle swarm optimization
Published 2024-12-01“…Comparison of GA-IPSO technique with other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Improved Grey Wolf Optimization (IGWO) and Differential Evolution Algorithm (DEA) showed that the proposed hybrid technique was superior and more efficient in solving the FACTS optimization problem.…”
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Optimizing Electric Vehicle Charging with Moth Flame Control Algorithm of Boost-KY Converter
Published 2023-11-01Get full text
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms
Published 2025-06-01Get full text
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024-12-01“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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REVIEW OF FEATURE SELECTION METHODS USING OPTIMIZATION ALGORITHM (Review paper for optimization algorithm)
Published 2023-09-01Get full text
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting
Published 2025-01-01“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment
Published 2023-08-01“…This analysis incorporates restrictions such as line loads, bus voltage influence, generator, line limits, etc. The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. …”
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An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm
Published 2025-01-01“…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
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Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model
Published 2025-08-01“…The results show that WOA can significantly improve the stability and convergence speed of the MCMC algorithm, the updating efficiency can be improved by 13.9% at most, and the maximum frequency errors of the simply supported beam model and the three-story steel frame model updated by the WO-MH algorithm are 0.009% and 2.41%, respectively. …”
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Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms
Published 2025-01-01“…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization
Published 2025-07-01“…Second, the inertia weights and learning factors of the standard PSO are improved to ensure the global search ability exhibited by the algorithm in the early stage and the ability to rapidly obtain the optimal solution in the later stage; we also introduce an adaptive variation algorithm in the particle search process to prevent the particles from being caught in local optima. …”
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