A highly generalized federated learning algorithm for brain tumor segmentation by Jun Wen, Xiusheng Li, Xin Ye, Xiaoli Li, Hang Mao

“…To address these issues, this paper proposes a client-side brain tumor image segmentation model utilizing Virtual Adversarial Training (VAT) integrated into a 3D U-Net to improve model performance under conditions of limited datasets, effectively addressing data scarcity and imbalance within the federated learning environment by optimizing the use of brain tumor image data held by each client. …”
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Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering by Qingdu Li, Keting Fu, Jian Liu, Yishan Li, Qinze Ren, Kang Xu, Junxiu Fu, Na Liu, Ye Yuan

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Research on the optimal scheduling of a multi-storage combined integrated energy system based on an energy supply grading strategy by Na Zhang, Feng You, Bingqian Hu, Jingyu Li, Guangchen Liu

“…Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. …”
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Design of optimized single-switch capacitor cell balancing for EV battery management by Anjan N. Padmasali, Savitha G. Kini, Arun P. Parameswaran

“…However, there are possible modifications to them that may lead to algorithms with improved results. Two algorithms are explored for a four-series connected Li-ion cell battery system. …”
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Nonlinear Optimization and Adaptive Heuristics for Solving Irregular Object Packing Problems by János D. Pintér, Ignacio Castillo, Frank J. Kampas

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Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…By integrating Principal Component Analysis (PCA)<i>,</i> hyperparameter optimization, and resampling methods, as well as combining Edited Nearest Neighbors (<i>ENN</i>) with the Synthetic Minority Oversampling Technique (SMOTE), the model significantly improves predictive accuracy and model generalization. …”
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Design and Optimization of Brushless Hybrid Wound Rotor Vernier Motor for Variable Speed Applications by Kapeel Kumar, Qasim Ali, Sheeraz Ahmed, Muhammad Ilyas, Hanlin Zhan, Mudassir Raza Siddiqi

“…To find out the optimal shape of the magnets, the Genetic algorithm optimization technique is used. …”
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Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

“…Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss analysis and predictive models based on Random Forest (RF) and K-Nearest Neighbors (KNN) algorithms. …”
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Risk-managed economic dispatch in hybrid hydrothermal-wind-solar systems: a novel multi-objective optimization approach by Zhe Wang, Tao Sun, Na Liu

“…A Multi-Objective Artificial Rabbits Optimization (MOARO) algorithm, incorporating Pareto criteria and fuzzy theory, is applied to optimize dispatch decisions while balancing cost and risk. …”
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Mapping and interpretability of aftershock hazards using hybrid machine learning algorithms by Bo Liu, Haijia Wen, Mingrui Di, Junhao Huang, Mingyong Liao, Jingyuan Yu, Yutao Xiang

“…By employing the stacking algorithm to optimize and combine XGBoost and LightGBM models, the proposed model significantly improves the prediction performance. …”
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A multi-modal feature combination mechanism for identification of harmonic load in distribution networks based on artificial intelligence models by Renzeng Yang, Shuang Peng, Gang Yao

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Optimization research on UAV semantic communication system based on SVD-MADRL by Yibo Yang, Yahe Tan, Liu Liu

“…The study optimizes the flight trajectory and power of multiple unmanned aerial vehicles with the deep deterministic policy gradient algorithm and constructs a multi-unmanned aerial vehicle semantic communication optimization model based on singular value decomposition and multi-agent deep reinforcement learning. …”
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AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…These limitations often lead to inefficiencies such as energy wastage, treatment delays, and overflow incidents, negatively impacting system performance and sustainability.AquaFlowNet leverages state-of-the-art machine learning algorithms to analyze real-time data from sensors, forecast flow variations, and optimize wastewater treatment processes. …”
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Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…With the widespread adoption of electric vehicles (EVs), optimizing their charging and discharging strategies to improve energy efficiency and extend battery life has become a focal point of current research. …”
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Optimizing Aircraft Routes in Dynamic Conditions Utilizing Multi-Criteria Parameters by Oleh Sydorenko, Nataliia Lysa, Liubomyr Sikora, Roman Martsyshyn, Yuliya Miyushkovych

“…In addition, optimal flight paths were modeled using the improved algorithms, which allow for increasing the efficiency of decision-making in the field of air traffic control. …”
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Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy by Haojie Ran, Dichen He, Huajun Tang

“…To solve this model, this study innovatively designs a hybrid algorithm combining neighborhood search and swarm intelligence, integrating the advantages of local exploration and global optimization to balance the relationships among multiple objectives efficiently. …”
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Advances to IoT security using a GRU-CNN deep learning model trained on SUCMO algorithm by Amit Sagu, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, Piyush Kumar Shukla, Mohd Asif Shah

“…The SUCMO algorithm fine-tunes the deep learning model’s hyperparameters to improve classification accuracy. …”
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Computer-Driven Assessment of Weighted Attributes for E-Learning Optimization by Olga Ovtšarenko, Elena Safiulina

“…Using artificial intelligence for data analytics, computer-based assessment improves efficiency, accuracy, and optimization of learning across disciplines. …”
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FAULT DIAGNOSIS METHOD OF SUBMERSIBLE SEWAGE PUMP BASED ON IMPROVED HOPFIELD NEURAL NETWORK by WANG Hui, LI NanQi, YANG ZhiPeng, ZHAO GuoChao, TIAN LiYong

“…The connection weights of HNN neural network were optimized by particle swarm optimization（PSO） algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. …”
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Dynamic multi-criteria scheduling algorithm for smart home tasks in fog-cloud IoT systems by Ruchika Bhakhar, Rajender Singh Chhillar

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