Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…To overcome these limitations, PCA is applied to minimize the dimensionality of the S11 response data, keeping only the most relevant information while improving computational efficiency. …”
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Robust Optimization for Microgrid Management With Compensator, EV, Storage, Demand Response, and Renewable Integration by Hamid Hematian, Mohamad Tolou Askari, Meysam Amir Ahmadi, Mahmood Sameemoqadam, Majid Babaei Nik

“…This paper presents an advanced two-stage robust day-ahead optimization model designed specifically for MG operations. …”
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MEIS-YOLO: Improving YOLOv11 for efficient aerial object detection with lightweight design by Yicheng Liu, Jinsong Wu, Li Chen

“…With the advancement of aerial technologies like drones and satellites, deep learning-driven object detection has seen considerable improvements in the processing of aerial images. Nevertheless, conventional object detection algorithms continue to encounter performance limitations, particularly when handling complex backgrounds and small objects. …”
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Iterative Optimization and Economic Analysis of Photovoltaic Power Generation Forecasting under Haze Conditions by Wei CHEN, Jing REN, Xinfang WU, Wenying YU, Yongsheng LIU

“…Through the revenue analysis of three photovoltaic economic models, the iterative optimization algorithm can improve the accuracy of photovoltaic revenue forecast.…”
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Forecast uncertainties real-time data-driven compensation scheme for optimal storage control by Arbel Yaniv, Yuval Beck

“…These advancements yield a reliable and efficient real-time correction algorithm for optimal site management, designed as an independent white box that can be integrated with any day-ahead optimization control system.…”
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Optimal design of frame structures equipped with viscous dampers using machine learning techniques by Yi Wen, Jianze Wang, Jun Xu, Kaoshan Dai, Yuanfeng Shi, Reza Sharbati

“…To achieve this, the proposed method involves the Machine Learning (ML) techniques of Extreme Gradient Boosting (XGBoost) and a Dynamic Programming (DP) algorithm. To generate the dataset for the XGBoost model development, an automated modeling and simulation tool for damping structures was developed. …”
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Research and Application of a Multi-Agent-Based Intelligent Mine Gas State Decision-Making System by Yi Sun, Xinke Liu

“…The system integrates the reasoning capabilities of LLMs and optimizes task allocation and execution efficiency of agents through the study of the hybrid multi-agent orchestration algorithm. …”
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RFID‐Based Enhanced Resource Optimization for 5G/6G Network Applications by Stella N. Arinze, Augustine O. Nwajana

“…These gains highlight the effectiveness of the RFID‐based optimization model in meeting the stringent performance requirements of 5G networks, particularly in high‐density deployments. …”
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The Evaluation and Promotion Strategy of TSC for Distribution System with New Energy under Power Market Environment by BAI Hao, WANG Yu-shan, ZHOU Chang-cheng, PAN Shu-hui, YE lin-hao, CAI Jian-yi

“…Finally, for scenarios where the TSC does not meet the standard, the improved PSO optimization algorithm is used to re-dispatch and improve TSC. …”
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Hybrid intelligence framework for optimizing shear capacity of lightweight FRP-reinforced concrete beams by Iman Faridmehr, Moncef L. Nehdi, Mohammad Ali Sahraei, Kiyanets Aleksandr Valerievich, Chiara Bedon

“…Leveraging a dataset of 260 experimental FRP-RC beam cases, two distinct Artificial Neural Network (ANN) models were developed using the Levenberg-Marquardt algorithm. …”
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Optimizing frequency stability with adaptive fast frequency reserves and Wide-Area Monitoring Systems by Bwandakassy Elenga Baningobera, Irina Oleinikova, Kjetil Uhlen

“…The adaptive algorithm’s ability to adjust to varying system conditions reduces the risk of over-shedding or under-shedding loads, thereby optimizing the system’s performance. …”
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UCA-YOLOv8n: a real-time and efficient fruit chunks detection algorithm for meal-assistance robot by Fei Liu, Mingyue Hu

“…Methods We propose an improved YOLOv8n algorithm optimized for real-time, high-accuracy fruit chunk detection. …”
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Optimal Coordination of Directional Overcurrent Relays in Microgrids Considering European and North American Curves by León F. Serna-Montoya, Sergio D. Saldarriaga-Zuluaga, Jesús M. López-Lezama, Nicolás Muñoz-Galeano

“…The proposed model is formulated as a mixed-integer nonlinear programming problem and solved using four metaheuristic techniques: the genetic algorithm (GA), Imperialist Competitive Algorithm (ICA), Harmonic Search (HS), and Firefly Algorithm (FA). …”
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Underwater Acoustic Signal Prediction Based on MVMD and Optimized Kernel Extreme Learning Machine by Hong Yang, Lipeng Gao, Guohui Li

“…Based on the prediction model of kernel extreme learning machine (KELM), this paper uses grey wolf optimization (GWO) algorithm to optimize and select its regularization parameters and kernel parameters and proposes an optimized kernel extreme learning machine OKELM. …”
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An Enhanced Distribution System Performance with Optimization Techniques for Location of Electrical Vehicle Charging Stations by Sainadh Singh Kshatri, Venkata Anjani Kumar G, Chilakapati Lenin Babu, Palepu Suresh Babu

“…The proposed methodology leverages the Grey Wolf Optimization (GWO) metaheuristic algorithm, enthused by the grey wolves hunting, to identify the most strategic locations for EVCSs. …”
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Bearing remaining useful life prediction based on optimized VMD and BiLSTM-CBAM. by Wei Liu, Sen Liu

“…To address the issue of low accuracy in existing remaining useful life (RUL) prediction algorithms for rolling bearings, this paper proposes a novel RUL prediction method based on the Beluga Whale Optimization (BWO) algorithm, Variational Mode Decomposition (VMD), an improved Convolutional Block Attention Module (CBAM*), and a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Comprehensive Utilization and Optimal Allocation of Environmental Protection Building Materials in the Construction of Civil Engineering by Li Ren, Huasha Ru, Ruiya Xiao, Yao Ju

“…The research methodology includes a multi-criteria decision-making approach, integrating material selection criteria such as mechanical properties, sustainability, cost, and environmental impact. An optimization model, using genetic algorithms and life cycle assessment, was employed to achieve the best material distribution for specific project needs. …”
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Enhancement method of series hybrid ship energy efficiency for speed and energy collaborative optimization by Yupeng Yuan, Xiaoyu Wang, Liang Tong, Chengqing Yuan, Boyang Shen, Teng Long

“…Afterwards, the optimised speed of the ship and the optimised output power of each power source were determined using the grasshopper optimization algorithm. The ship's energy efficiency levels before and after using the energy efficiency enhancement method were compared and analysed, and the effects of this optimization method on the ship's energy efficiency in several typical voyages were analysed. …”
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Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

“…Abstract The growing need for sustainable energy sources and stricter environmental regulations necessitate the development of alternative fuels with lower emissions and improved performance. This study addresses these challenges by optimizing the performance and emission characteristics of a single-cylinder diesel engine powered by neem oil biodiesel blends enhanced with alumina nanoparticlesusing the powerful desirability-based optimization. …”
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Prediction and dynamic optimization of drilling performance based on the combination of mineral composition and operational factors by Xiong Xiuli, Li Qian, Liu Junhao, Jiang Jie

“…According to the training and testing results, the introduction of mineral composition can effectively improve the training speed and testing accuracy. Through the established prediction function, a dynamic optimization algorithm combined with DOE (Design of Experiments) theory was also developed. …”
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