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Enhancing Solid Oxide Fuel Cell Efficiency Through Advanced Model Identification Using Differential Evolutionary Mutation Fennec Fox Algorithm
Published 2025-02-01“…This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). …”
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62
An Efficient Hybrid Meta-heuristic Algorithm for Solving Capacitated Vehicle Routing Problem
Published 2025-06-01Get full text
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63
A Novel Genetic Algorithm for Constrained Multimodal Multi-Objective Optimization Problems
Published 2025-06-01“…Additionally, three environmental selection strategies are designed to correspond to the different tasks in MTGA-CMMO. Extensive experimental verification demonstrates that MTGA-CMMO outperforms other comparative algorithms across multiple test instances and one practical application problem.…”
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64
Optimization of Rendering Parameters of Cesium 3DTiles Model Based on Differential Evolution Algorithm
Published 2025-01-01Get full text
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65
Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs
Published 2025-01-01“…The proposed technique is tested across different simulation scenarios, movement models, and parameter configurations and is compared to our genetic algorithm ‘Genetic Algorithm-Aerial Paths’ (GA-AP) counterpart to evaluate its effectiveness.…”
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66
Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species
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67
Solving a low-carbon routing problem for perishable distribution food
Published 2024-12-01“…The Cycle evolutionary algorithm can quickly and effectively seek the optimal solution of the model. …”
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68
Multi-Objective Optimization of Urban Air Transportation Networks Under Social Considerations
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Evolutionary Optimization of Multirendezvous Impulsive Trajectories
Published 2021-01-01“…This paper investigates the use of evolutionary algorithms for the optimization of time-constrained impulsive multirendezvous missions. …”
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71
Learning-Driven Algorithm With Dual Evolution Patterns for Solving Large-Scale Multiobjective Optimization Problems
Published 2025-01-01“…Among them, learning-driven evolutionary algorithms have shown to be promising by learning the related evolutionary pattern with a specific neural network. …”
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72
Bio-Inspired Multiobjective Optimization for Designing Content Distribution Networks
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73
A multi-population multi-objective maritime inventory routing optimization algorithm with three-level dynamic encoding
Published 2025-04-01“…In this paper, the proposed MP-MOEA is compared with five state-of-the-art multi-objective evolutionary algorithms, including NSGAII, BiCo, MSCEA, TSTI, and AGEMOEAII, on maritime inventory routing problems of three different scales. …”
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74
A Pipeline for Multivariate Time Series Forecasting of Gas Consumption in Pelletization Process
Published 2025-05-01“…In the final stage, two AutoML approaches were employed: neural architecture search using AutoKeras and the DEAP (Distributed Evolutionary Algorithm) framework. The neural network architectures tested included MLP, RNN, LSTM, and Conv1D. …”
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75
RETRACTED ARTICLE: Machine learning intelligent based hydromagnetic thermal transport under Soret and Dufour effects in convergent/divergent channels: a hybrid evolutionary numeric...
Published 2023-12-01“…To optimize the weights and biases of artificial neural networks (ANNs), employ a hybridization of advanced evolutionary optimization algorithms, specifically the artificial bee colony (ABC) optimization integrated with neural network algorithms (NNA). …”
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Neuro-evolutionary models for imbalanced classification problems
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77
Learning and Evolution: Factors Influencing an Effective Combination
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78
Metaheuristic-Based Model Optimization of a Steam-Filled Chamber
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79
A surrogate-assisted differential evolution algorithm with a dual-space-driven selection strategy for expensive optimization problems
Published 2025-04-01“…Abstract Surrogate-assisted evolutionary algorithms (SAEAs) have shown great potential to solve computationally expensive optimization problems (EOPs). …”
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Prediction of Drifter Trajectory Using Evolutionary Computation
Published 2018-01-01“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. As the evaluation measure, a method that gives a better score as the Mean Absolute Error (MAE) when the difference between the predicted position in time and the actual position is lower and the Normalized Cumulative Lagrangian Separation (NCLS), which is widely used as a trajectory evaluation method of drifters, were used. …”
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