An optimized proportional resonant current controller based genetic algorithm for enhancing shunt active power filter performance by Behnam Amini, Hasan Rastegar, Mohammad Pichan

“…Therefore, by performing accurate and optimal adjustments for APF control, system performance and power quality level can be improved significantly. …”
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AI-Driven Identification of Grapevine Fungal Spores via Microscopic Imaging and Feature Optimization with Cuckoo Search Algorithm by Xin Shi, Seyed Mohamad Javidan, Yiannis Ampatzidis, Zhao Zhang

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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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RE-BPFT: An Improved PBFT Consensus Algorithm for Consortium Blockchain Based on Node Credibility and ID3-Based Classification by Junwen Ding, Xu Wu, Jie Tian, Yuanpeng Li

“…Experimental results indicate that RE-BPFT markedly reduces consensus latency and communication costs while achieving higher throughput and better scalability than classical PBFT, RBFT, and PPoR algorithms. …”
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Optimizing Human-Centric Warehouse Operations: A Digital Twin Approach Using Dynamic Algorithms and AI/ML by Erhan Arslan

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Optimizing Container Repositioning Using a Sequential Insertion Algorithm for Pickup-Delivery Routing in Export-Import Operations by Ary Arvianto, Dihan Chofifah Cahyani, Dhimas Wachid Nur Saputra

“…The increasing number of empty containers significantly causes to traffic congestion and rising operational costs, thereby necessitating the development of an optimized routing model to enhance fleet utilization and minimize transportation expenses. …”
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Research on run-time overhead of RM and improvement by LUO Ding-ding, ZHAO Hai, SUN Pei-gang, ZHANG Xi-yuan, YIN Zhen-yu

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A multi-population multi-objective maritime inventory routing optimization algorithm with three-level dynamic encoding by Tianyu Liu, Jiaping Liu, He Xu

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Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy by Yangqing DAN, Lei WANG, Weimin ZHENG, Jiahui WU, Chenxuan WANG, Gaowang YU

“…And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. …”
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An improved permeability estimation model using integrated approach of hybrid machine learning technique and Shapley additive explanation by Christopher N. Mkono, Chuanbo Shen, Alvin K. Mulashani, Patrice Nyangi

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A Non-Rigid Three-Dimensional Image Reconstruction Algorithm Based on Deformable Shape Reliability by Haiying Chen, Syed Atif Moqurrab

“…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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Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…Our research integrates a priori knowledge of threat zone locations, speeds, and directions with real-time data on the UAVs position relative to the threat zones to effectively manage dynamic threat zones, allowing UAVs to dynamically decide whether to navigate around or through these zones, thus significantly reducing trajectory costs. To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…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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Effects of off-design performances and multiple market carbon trading mechanism on integrated energy systems with waste incineration power units by Jing Liu, Tong Zhao, Haolin Sui

“…Furthermore, to analyze effects of off-design performances and MMCTM on the electricity-gas-heating-cooling IES, five case studies have been conducted on a typical electricity-gas-heating-cooling IES and the improved slime mould algorithm (ISMA) were adopted. …”
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Advanced AI approaches for the modeling and optimization of microgrid energy systems by Mohammed Amine Hoummadi, Badre Bossoufi, Mohammed Karim, Ahmed Althobaiti, Thamer A. H. Alghamdi, Mohammed Alenezi

“…Three AI techniques, Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO), are employed to optimize the optimal composition of energy sources based on solar energy and wind energy, battery storage, and load profiles. …”
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Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning by I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin

“…However, these methods have not performed well with classical machine learning algorithms. Methods To optimize the performance of classical machine learning on customer churn prediction tasks, this study introduces an extension framework called CostLearnGAN, a tabular generative adversarial network (GAN)-hybrid sampling method, and cost-sensitive Learning. …”
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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…MaOSSO is shown to consistently outperform competing methods with up to 15–20% faster convergence and 25% less computation time. While applying the algorithm on the MaO-OPF problem, the active/reactive power loss minimization was optimized along with the voltage stability, emissions, operational cost, and Pareto front diversity sustaining. …”
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A Chaotic Decomposition-Based Approach for Enhanced Multi-Objective Optimization by Javad Alikhani Koupaei, Mohammad Javad Ebadi

“…To address these issues, this paper proposes a chaotic decomposition-based approach that leverages the ergodic properties of chaotic maps to enhance optimization performance. The proposed method consists of three key stages: (1) chaotic sequence initialization, which generates a diverse population to enhance the global search while reducing computational costs; (2) chaos-based correction, which integrates a three-point operator (TPO) and a local improvement operator (LIO) to refine the Pareto front and balance the exploration–exploitation trade-offs; and (3) Tchebycheff decomposition-based updating, ensuring efficient convergence toward optimal solutions. …”
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IoT driven healthcare monitoring with evolutionary optimization and game theory by Shitharth Selvarajan, Hariprasath Manoharan, Taher Al-Shehari, Nasser A. Alsadhan, Subav Singh

“…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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