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Employment of a Radial Basis Function Model for Predicting the Heating Load of Construction
Published 2025-04-01“…The innovative approaches presented in this research consist of integrating 2 advanced optimizers, namely an Improved Manta-Ray Foraging Optimizer (IMRFO) and a Population-based Vortex Search Algorithm (PVSA), with a Radial Basis Function (RBF). …”
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A Non-Rigid Three-Dimensional Image Reconstruction Algorithm Based on Deformable Shape Reliability
Published 2024-01-01“…Most reconstruction algorithms for non-rigid three-dimensional (3D) images assume that non-rigidity can be represented as a linear combination of a fixed number of rigid bases. …”
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224
A Model Predictive Control to Improve Grid Resilience
Published 2025-04-01“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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225
Improving with Hybrid Feature Selection in Software Defect Prediction
Published 2024-04-01“…Feature selection is often used by some researchers to overcome these problems, because these methods have an important function in the process of reducing data dimensions and eliminating uncorrelated attributes that can cause noisy. Naive Bayes algorithm is used to support the process of determining the most optimal class. …”
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226
IoT driven healthcare monitoring with evolutionary optimization and game theory
Published 2025-04-01“…By incorporating two evolutionary algorithms, the proposed approach optimizes the state of action for each participant while reducing energy consumption and processing delay. …”
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227
Multi-objective multi-workflow task offloading based on evolutionary optimization
Published 2025-08-01“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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228
Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence
Published 2024-10-01Get full text
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A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization
Published 2025-04-01“…A modified Grey Wolf Optimization algorithm with three significant adjustments improves feature selection and redundancy removal over the previous approach. …”
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231
Optimal ecological restoration strategy development based on value-cost trade-offs
Published 2025-04-01“…In addition, we searched for Pareto-optimal solutions using the nondominated sorting genetic algorithm II (NSGA-II) to balance the trade-offs between different objectives. …”
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An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid
Published 2025-05-01“…EMS is a control system integrated within MGs for managing the operations of these DGs effectively to fulfill a power balance between power production and load demand in the most optimal way, especially in island MGs. In this paper, an EMS based on Multiple Adaptive Neuro-Fuzzy Inference System optimized by Genetic Algorithm (MANFIS-GA) is proposed for PV/Wind/Diesel Generator/Battery (PWDB) island MG system, to optimize the output power of diesel generator, manage charging-discharging operation of MG Battery Storage keeping its State of Charge (SOC) in acceptable limits, and improve the MG system reliability and stability by mitigating the effects of sudden changes in the electrical loading and Renewable energy sources (RES) Power. …”
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234
Optimizing laser powder bed fusion parameters for enhanced hardness of Ti6Al4V alloys: A comparative analysis of metaheuristic algorithms for process parameter optimization
Published 2025-04-01“…Given its simplicity alongside its accuracy and robust performance, the JAYA algorithm proves the most appropriate method for LPBF parameter optimization. …”
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235
Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks
Published 2025-05-01“…The methodology consists of three key phases: (1) Data preprocessing, where missing values are handled using the multiple imputations by chain equation (MICE) technique and feature scaling is applied using standard and min-max scalers; (2) Feature selection, where the FFXO algorithm reduces feature dimensionality to enhance classification efficiency; and (3) Lung tumor classification, utilizing Bi-GAN to improve predictive accuracy. …”
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236
Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks
Published 2025-09-01“…A novel heuristic, the Modernized Pufferfish Optimization Algorithm (MPOA), is introduced to optimize WSN performance, drawing inspiration from the pufferfish's natural defense strategies. …”
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237
Beyond boundaries: AI-optimized global landslide susceptibility mapping
Published 2025-12-01“…This study addresses these gaps by developing an optimized framework using support vector regression (SVR) enhanced with meta-heuristic algorithms (grey wolf optimizer [GWO] and bat algorithm) to refine model hyper-parameters. …”
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A novel feature selection algorithm using decomposition based multi-objective guided honey badger algorithm (MO-GHBA) and NSGA-III
Published 2023-04-01“…In most of the MOEAs based feature selection algorithms, more optimal solutions are obtained around the Pareto front's center because of the deficiency in selection features. …”
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Optimization Models for Reducing the Air Pollutants Emission in the Production of Insulation Bituminous
Published 2023-05-01“…According to the optimization results, the most suitable air temperature and percent excess air were selected to achieve the lowest pollutant emissions. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection
Published 2025-12-01“…It also requires fewer parameters and takes minimum training time. • The major contribution of this study is the design of an optimized, efficient and enhanced deep learning technique for multiclass rice crop disease detection embracing with batch normalization, dropout and genetic optimization algorithm to improve generalization power and restrict the overlearning capability for seen and unseen data. • Proposed VCNet, a shallow model with deep feature extraction, employs VGG16 layers for initial extraction fused with custom CNN architecture to correctly detect the challenging classes of diseases like sheath rot in multiclass classification. • The most significant observation is that VCNet accurately predicts the rice disease for each class of diseases under study whereas the existing powerful models largely misclassified for some classes of diseases in multiclass classification.…”
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