Control and Stability Analysis of Double Time-Delay Active Suspension Based on Particle Swarm Optimization by Kaiwei Wu, Chuanbo Ren

“…So, it is indicating that the active suspension with double time-delay feedback control has a better control effect in improving the ride comfort of the car, and it has important reference value for further research on suspension performance optimization.…”
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Multi-Objective Parameter Optimization of Electro-Hydraulic Energy-Regenerative Suspension Systems for Urban Buses by Zhilin Jin, Xinyu Li, Shilong Cao

“…To streamline multi-objective optimization processes, a particle swarm optimization–back propagation (PSO-BP) neural network surrogate model was developed to approximate the complex co-simulation system. …”
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Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network by Renpeng LIU, Bo HU, Hequn LI

“…The high-speed motion of low-earth orbit communication satellites results in a highly dynamic network topology, and the spatio-temporal distribution of resources in the satellite-terrestrial integrated network is non-uniform.When multiple users and services switch between satellites, a large number of handover requests are triggered, leading to intensified network resource competition.As a result, the limited satellite resources cannot meet all the handover requests, leading to a significant decrease in handover success rate.In view of the above problem, the multi-objective optimization based satellite handover method was proposed.It introduced the satellite coverage spatio-temporal graph and transforms the dynamic continuous topology into static discrete snapshots, accurately depicted the connections between satellite nodes and users at different times and locations.The multi-objective optimization model was established for satellite handover decisions, and anadaptive accelerated multi-objective evolutionary algorithm(AAMOEA) was proposed to optimized user data rate and network load simultaneously, ensured handover success rate and enhanced network service capability.It built a STIN communication simulation environment and tested the multi user handover performance in a multi satellite overlapping coverage scenario.The results demonstrated that the multi-objective optimization-based satellite handover method achieved an average handover success rate improvement of over 20% compared to benchmark algorithms.…”
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A Reinforcement Learning Approach to Personalized Asthma Exacerbation Prediction Using Proximal Policy Optimization by Dahiru Adamu Aliyu, Emelia Akashah Patah Akhir, Maryam Omar Abdullah Sawad, Jameel Shehu Yalli, Yahaya Saidu

“…The model achieved 96.60% accuracy, 95.79% precision, 96.65% recall, and 95.92% F1-score, outperforming baseline RL algorithms such as Deep Q-Learning (92.21% accuracy), Advantage Actor-Critic (94.34% accuracy), and Trust Region Policy Optimization (95.12% accuracy). …”
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Advancing Smart Energy: A Review for Algorithms Enhancing Power Grid Reliability and Efficiency Through Advanced Quality of Energy Services by José M. Liceaga-Ortiz-De-La-Peña, Jorge A. Ruiz-Vanoye, Juan M. Xicoténcatl-Pérez, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Ricardo A. Barrera-Cámara, Daniel Robles-Camarillo, Marco A. Márquez-Vera, Francisco R. Trejo-Macotela, Luis A. Ortiz-Suárez

“…By concentrating on key aspects—reliability, availability and operational efficiency—the study reviews how various algorithmic approaches, from machine learning models to classical optimisation techniques, can significantly improve power grid management. …”
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Study on the peak shaving operation of cascade hydropower stations based on the plant-wide optimal curve by Fengshuo Liu, Kui Huang, Xuanyu Shi, Longqing Zhao, Yangxin Yu, Xueshan Ai, Xiang Fu

“…This study proposes a novel method to enhance RES and hydropower utilization through: 1) Establishing a plant-wide optimal output-water level-outflow relationship curve based on the output-head-flow relationship and the flow-head loss and outflow-tailwater level relationship curves for each unit; 2) Developing a short-term peak shaving model for cascaded hydropower stations that incorporates wind and PV power which defines minimum coefficient of variation of residual load as objective functions, and improving discrete differential dynamic programming successive approximation (DDDPSA) method to solve it; 3) Analyzing the peak shaving capacity of the cascade hydropower station by varying water consumption for power generation. …”
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Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning by Yi Xu, Mohd Hairi Mohd Zaman, Feng Zhou

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Adaptive RFID Data Scheduling Using Proximal Policy Optimization for Reducing Data Processing Latency by Guowei Guo, Xinsen Yang, Ziwei Liang, Zeli Xi, Ximei Zhan, Peisong Li

“…This paper presents a novel approach for dynamically offloading data using deep reinforcement learning, specifically employing the Proximal Policy Optimization (PPO) algorithm. The proposed method utilizes a central controller equipped with the PPO model to make intelligent, real-time reader selection decisions based on environmental factors such as reader load, tag mobility, and network conditions. …”
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Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…Additionally, we examine the computational complexity of this model and propose two solution algorithms grounded in fixed-parameter tractability theory for specific network classes.…”
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Advancing Arabic Word Embeddings: A Multi-Corpora Approach with Optimized Hyperparameters and Custom Evaluation by Azzah Allahim, Asma Cherif

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An Edge Container Migration Optimization Method for Multi-service Intelligent Resource Scheduling of Distribution Networks by Shuai LI, Di XU, Xiangyu WEN, Jiaxin ZHANG

“…The simulation results demonstrate that compared with traditional algorithms, the proposed method can validly improve the data processing delay performance for distribution network.…”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Multi sensor based monitoring of paralyzed using Emperor Penguin Optimizer and Deep Maxout Network by Vijaya Gunturu, J. Kavitha, Swapna Thouti, N. K. Senthil Kumar, Kamal Poon, Ayman A. Alharbi, Amar Y. Jaffar, V. Saravanan

“…The Emperor Penguin Optimizer Algorithm (EPOA) was used to select the features sent from the Arduino board to the ESP8266-Wi-Fi module. …”
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Continuously Variable Geometry Quadrotor: Robust Control via PSO-Optimized Sliding Mode Control by Foad Hamzeh, Siavash Fathollahi Dehkordi, Alireza Naeimifard, Afshin Abyaz

“…A sliding mode control algorithm, optimized using particle swarm optimization, is implemented to ensure stability and high performance in the presence of uncertainties and noise. …”
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Cooperative and Hierarchical Optimization Design of Shipboard MVDC System for Adapting to Large, Pulsed Power Load by Zhimeng Liu, Yongbao Liu, Youhong Yu, Rui Yang

“…The hierarchical optimization model is designed with energy storage configuration and dynamic performance as the lower and upper objectives, and an efficient parallel neural network-based genetic algorithm is employed to solve this optimization. …”
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Developing an Equitable Machine Learning–Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation by Chelsea S Brown, Luna Dziewietin, Virginia Partridge, Jennifer Rae Myers

“…Aim 2 is to develop knowledge embedding–based machine learning (ML) models that use music metadata and survey response data to identify optimal therapeutic music components for enhancing engagement and emotional resonance for depression among rural-residing older adults at risk for AD. …”
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Design of experiments for the stochastic unit commitment with economic dispatch models by Nahal Sakhavand, Jay Rosenberger, Victoria C.P. Chen, Harsha Gangammanavar

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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…The YOLOv10-BCE panting behavior detection model was developed by embedding the BiFormer module into the backbone network to enhance multi-dimensional feature extraction, compressing neck structure parameters using the C3Ghost module, and integrating Efficient Intersection over Union (EIOU) loss to improve detection accuracy and convergence speed. …”
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Bi-directional virtual search algorithm for efficient and collision-free path planning in autonomous robots navigating static and dynamic environments by M.D. Yeshwanth Kumar, K. Rajchandar

“…Extensive experiments were conducted across multiple static and dynamic scenarios. The proposed model achieved a path efficiency improvement of 17.9 % and a computational time reduction of 23.4 % compared to traditional A* and Dijkstra’s algorithms. …”
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On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability by Tapasi Brahma, Alexander Guillen, Jeffrey Moreno, Abhishek Datta, Yu Huang

“…Material and method: Here we aim to study the inter-individual variability of optimized TI by applying the same optimization algorithms on N = 25 heads using their individualized head models. …”
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