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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm
Published 2025-01-01“…This approach improved the accuracy and robustness of structural parameter identification while maintaining computational efficiency.MethodsMOMDBA is an enhanced version of the Directional Bat Algorithm (DBA), a swarm intelligence optimization technique inspired by the echolocation behavior of bats. …”
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723
Research on the construction of English vocabulary learning recommendation system based on multi-objective crow search algorithm
Published 2025-12-01“…Regarding the experiments, we compared MOCSO with traditional single - objective optimization algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). 56.4 % of users believe that the recommended vocabulary content meets their deep learning needs, while 18.2 % of learners hope that the system can further improve the practical application ability of vocabulary. …”
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724
Predicting CO<sub>2</sub> Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm
Published 2025-04-01“…In this paper, we propose a general framework that combines advanced deep learning models (such as GRU, Bidirectional GRU (BIGRU), Stacked GRU, and Attention-based BIGRU) with a novel hybridized optimization algorithm, GGBERO, which is a combination of Greylag Goose Optimization (GGO) and Al-Biruni Earth Radius (BER). …”
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725
A New Method for Spectral Wavelength Selection Based on Multiple Linear Regression Combined with Ant Colony Optimization and Genetic Algorithm
Published 2022-01-01“…Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces the computation time while also improving the prediction accuracy of the model. …”
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726
Optimizing Autonomous Multi-UAV Path Planning for Inspection Missions: A Comparative Study of Genetic and Stochastic Hill Climbing Algorithms
Published 2024-12-01“…GA exemplifies the global search strategy, while HC illustrates an enhanced stochastic local search. …”
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727
Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms
Published 2024-12-01“…Machine learning helps in predicting the optimal parameters, whereas nanofluids enhance cooling efficiency while preserving both the tool and the workpiece. …”
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728
Optimum design of double tuned mass dampers using multiple metaheuristic multi-objective optimization algorithms under seismic excitation
Published 2025-03-01“…However, implementing multiple-tuned mass dampers can also improve seismic performance while reducing the required mass. …”
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729
Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm
Published 2025-08-01“…In the first phase, predictive modeling was performed using multilayer perceptron neural networks (MLPNN) optimized by three metaheuristic algorithms: cheetah optimizer (CO), grey wolf optimizer (GWO), and marine predators algorithm (MPA). …”
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730
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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters
Published 2024-12-01“…This paper introduces a novel hyperparameter optimization framework for regression tasks called the Combined-Sampling Algorithm to Search the Optimized Hyperparameters (CASOH). …”
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732
Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system
Published 2022-09-01“…A new classification model of electrocardiogram (ECG) signal based on particle swarm optimization feature selection (PSOFS) and TSK (Takagi-Sugeno-Kang) fuzzy system was proposed, i.e., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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733
Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance
Published 2025-03-01“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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734
Optimizing Vehicle Routing for Perishable Products with Time Window Constraints:
Published 2025-01-01Get full text
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735
Improving the area-preserving parameterization of rational Bézier surfaces by rational bilinear transformation
Published 2025-08-01“…To improve the area-preserving parameterization quality of rational Bézier surfaces, an optimization algorithm using bilinear reparameterization is proposed. …”
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736
Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer
Published 2025-04-01“…This paper proposes a Kalman filter-based cascaded PI-(1+PI) controller, optimized using an Improved Spider Wasp Optimizer (ISWO), to address the challenges of USV heading control in dynamic marine environments. …”
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737
Puma algorithm for environmental emissions and generation costs minimization dispatch in power systems
Published 2025-03-01“…It efficiently navigates the solution space by balancing exploration and exploitation, leveraging puma-like intelligence to minimize both fuel costs and greenhouse gas emissions, including CO2, NOx, and SO2. The POO algorithm is tested on the IEEE 30-bus power system with six thermal units, delivering superior performance compared to advanced optimization algorithms such as the Osprey Optimization Algorithm (OOA), Aquila Optimizer (AO), Slim Mould Algorithm (SMA), Artificial Rabbit Optimization (ARO), and Coati optimization technique. …”
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738
Dam Deformation Data Preprocessing with Optimized Variational Mode Decomposition and Kernel Density Estimation
Published 2025-02-01“…The approach systematically processes data in three steps: First, VMD decomposes raw data into intrinsic mode functions without recursion. The parallel Jaya algorithm is used to adaptively optimize VMD parameters for improved decomposition. …”
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739
Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm
Published 2024-12-01“…The research problem focuses on improving the effectiveness and computational efficiency of energy management systems (EMS) while ensuring high system reliability. …”
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740