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301
Design and Analysis of SSSC-Based Damping Controller: A Novel Modified Zebra Optimization Algorithm Approach
Published 2024-01-01“…The suggested study distinguishes between the mZOA method, traditional ZOA, and conventional PSO algorithms. Based on the simulation findings, it can be inferred that the modified approach that has been suggested is the most effective method for defining the said damping controller by considering the percentage improvement in the objective function value.…”
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302
Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III
Published 2025-01-01“…Finally, based on the obtained mathematical model, the 3rd Non-dominated Sorting Genetic Algorithm (NGSA-III) is used to adjust and optimize the control parameters. …”
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303
Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell
Published 2024-12-01“…The parameter combinations were then optimized synchronously using genetic algorithms to reduce the magnetic field gradient in the vapor cell region and enhance the magnetic noise self-suppression capability of the heater. …”
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304
Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm
Published 2021-01-01“…In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. …”
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305
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306
Optimizing machine learning algorithms for diabetes data: A metaheuristic approach to balancing and tuning classifiers parameters
Published 2024-09-01“…Leveraging Particle Swarm Optimization (PSO) algorithm for diabetes data balancing and a genetic algorithm to select the optimal architecture for various machine learning classifiers. …”
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307
Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects
Published 2021-01-01“…Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. …”
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308
Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics
Published 2024-09-01“…<b>Objectives:</b> The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. …”
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309
Classification Based on Brain Storm Optimization With Feature Selection
Published 2021-01-01“…Recently, some evolutionary algorithms (EAs) such as the fireworks algorithm (FWA) and brain storm optimization (BSO) algorithm have been employed to implement the evolutionary classification model and achieved the desired results. …”
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310
Enhancing image retrieval through optimal barcode representation
Published 2025-08-01Get full text
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311
Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms
Published 2025-06-01“…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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312
A Novel Black Widow Optimization Algorithm Based on Lagrange Interpolation Operator for ResNet18
Published 2025-06-01Get full text
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313
Developing a Machine Learning-Driven Model that Leverages Meta-Heuristic Algorithms to Forecast the Load-Bearing Capacity of Piles
Published 2023-12-01“…Additionally, it uses two separate meta-heuristic optimization methods, namely the Golden Jackal optimization algorithm (GJO) and Smell Agent Optimization (SAO), to achieve the best possible results. …”
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314
Charging path optimization in mobile wireless rechargeable sensor networks
Published 2023-12-01“…The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wireless sensor networks, which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers’ deployment or mobile chargers’ charging path for static sensor nodes with fixed sensor node positions, ignoring the scenario with mobile sensor nodes.Thus, design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes, to maximize the charging utility within a finite time horizon, that is, the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then, based on the constructed directed acyclic graph using discretization method, a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by layer-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility .…”
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315
Charging path optimization in mobile wireless rechargeable sensor networks
Published 2023-12-01“…The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wireless sensor networks, which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers’ deployment or mobile chargers’ charging path for static sensor nodes with fixed sensor node positions, ignoring the scenario with mobile sensor nodes.Thus, design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes, to maximize the charging utility within a finite time horizon, that is, the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then, based on the constructed directed acyclic graph using discretization method, a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by layer-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility .…”
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316
Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization
Published 2025-09-01“…This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. …”
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317
TBESO-BP: an improved regression model for predicting subclinical mastitis
Published 2025-04-01“…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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318
Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model
Published 2025-04-01“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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319
Parameter Extraction of Photovoltaic Cells and Panels Using a PID-Based Metaheuristic Algorithm
Published 2025-07-01Get full text
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320
An adaptive hybrid framework for IIoT intrusion detection using neural networks and feature optimization using genetic algorithms
Published 2025-05-01“…Additionally, Genetic Algorithms were employed to optimize feature selection, further refining the ANN’s input space to improve computational efficiency without sacrificing predictive power. …”
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