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181
Improving Quantum Optimization Algorithms by Constraint Relaxation
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182
Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence
Published 2024-10-01Get full text
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183
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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184
An improved termite life cycle optimizer algorithm for global function optimization
Published 2025-02-01“…The termite life cycle optimizer algorithm (TLCO) is a new bionic meta-heuristic algorithm that emulates the natural behavior of termites in their natural habitat. …”
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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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187
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An electricity price optimization model considering time-of-use and active distribution network efficiency improvements
Published 2025-01-01“…To address the issues of high energy costs and inadequate system response speed in complex electricity markets, we propose an electricity price optimization model. This model combines an improved Particle Swarm Optimization algorithm, Quantum-behaved Particle Swarm Optimization, and the Shuffle Frog Leaping Algorithm. …”
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189
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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190
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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191
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“…Additionally, the absence of clustering in certain models compromises the network capacity. To tackle these challenges, a new multi-level clustering technique with a heuristic optimization algorithm is proposed in this research work. …”
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192
Improved Sparrow Search Algorithm for Sparse Array Optimization
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193
Data Decomposition Modeling Based on Improved Dung Beetle Optimization Algorithm for Wind Power Prediction
Published 2024-12-01“…To enhance prediction accuracy, this paper presents a hybrid wind power prediction model that integrates the improved complementary ensemble empirical mode decomposition (ICEEMDAN), the RIME optimization algorithm (RIME), sample entropy (SE), the improved dung beetle optimization (IDBO) algorithm, the bidirectional long short-term memory (BiLSTM) network, and multi-head attention (MHA). …”
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194
Application of Optimal Scheduling Model Based on Improved Genetic Algorithm in Electric Power Mobile Operation
Published 2024-01-01“…In order to solve the current situation, an optimized scheduling model for power mobile jobs based on improved genetic algorithm is proposed. …”
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195
Optimizing performance and economic viability of combined energy systems: A novel energy hub framework
Published 2025-06-01“…To solve this complex optimization problem, the spider monkey optimization (SMO) algorithm is modified and applied. …”
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196
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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197
Anti-Collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm
Published 2024-11-01“…Comparative analysis of visual trajectories pre-optimization and post-optimization highlights improvements. …”
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Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm
Published 2022-01-01“…The parametric mathematical model of the airfoil and aerodynamic parameter proxy model of airfoil were constructed using the Hicks-Henne improved function and CFD solution sample, focusing on the issues with particle swarm optimization algorithms such as slow convergence, a tendency to fall into local optimal solutions, and oscillation at a late stage; an optimization method for the low-speed airfoil of a small UAV based on improved particle swarm optimization was developed. …”
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200
A Novel Modified Gorilla Troops Optimizer Algorithm for Interline Power Flow Controller-Based Damping Controller Design
Published 2025-05-01“…To effectively dampen low-frequency oscillations, an auxiliary controller for modeling the IPFC is proposed. It provides four options for damping controllers, and the recommended mGTO algorithm is used to adjust the controller parameters. …”
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