Research on Automatic Tracking and Size Estimation Algorithm of “Low, Slow and Small” Targets Based on Gm-APD Single-Photon LIDAR by Dongfang Guo, Yanchen Qu, Xin Zhou, Jianfeng Sun, Shengwen Yin, Jie Lu, Feng Liu

“…The improved algorithm is stable in the 1250-frame tracking experiment of DJI Elf 4 UAV with a flying speed of 5 m/s and a flying distance of 100 m. …”
Get full text

Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

“…Each source image is guided through guided filtering using Gaussian curvature as guidance. While the detail layers are fused based on maximum energy assessed using the Krisch compass operator, the base layers are fused based on the whale optimization method,  for which the objective function is maximization of entropy, edge strength and pixel intensity. …”
Get full text

A cluster-optimized regulation method for distribution networks considering distributed photovoltaic heterogeneous characteristics by Junhao Li, Xin Wang, Qi Guo, Chunzhi Yang, Yizhe Chen, Ruifeng Zhao, Ming Li

“…To address these challenges, a cluster-optimized regulation method is proposed, leveraging DPV heterogeneity to enable coordinated regulation while reducing directly-managed devices through DN clustering. …”
Get full text

Model Predictive Control-Based Energy Management System for Cooperative Optimization of Grid-Connected Microgrids by Sungmin Lim, Jaekyu Lee, Sangyub Lee

“…While the isolated operation of individual MGs limits system-wide optimization, the proposed approach enhances both stability and efficiency through integrated control. …”
Get full text

Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…［Objective］ Re-coupling operation mode can effectively improve the matching degree between the passenger flow and the transport capacity of urban rail transit, while it also poses challenges to the formulation of the train stock utilization plan. …”
Get full text

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. …”
Get full text

An Intelligent Path Planning System for Urban Airspace Monitoring: From Infrastructure Assessment to Strategic Optimization by Qianyu Liu, Wei Dai, Zichun Yan, Claudio J. Tessone

Get full text

Fine-Grained Classification of Pressure Ulcers and Incontinence-Associated Dermatitis Using Multimodal Deep Learning: Algorithm Development and Validation Study by Alexander Brehmer, Constantin Seibold, Jan Egger, Khalid Majjouti, Michaela Tapp-Herrenbrück, Hannah Pinnekamp, Vanessa Priester, Michael Aleithe, Uli Fischer, Bernadette Hosters, Jens Kleesiek

Get full text

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. …”
Get full text

Optimizing a Double Stage Heat Transformer Performance by Levenberg–Marquardt Artificial Neural Network by Suset Vázquez-Aveledo, Rosenberg J. Romero, Lorena Díaz-González, Moisés Montiel-González, Jesús Cerezo

“…This study aims to simultaneously optimize both user-defined parameters. Levenberg–Marquardt and scaled conjugated gradient algorithms were compared from five to twenty-five neurons to determine the optimal operating conditions while the coefficient of performance and the gross temperature lift were simultaneously maximized. …”
Get full text

A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…This study proposes a hybrid forecasting model integrating variational mode decomposition (VMD), the Fruit Fly Optimization Algorithm (FOA), and a gated recurrent unit (GRU). …”
Get full text

Optimal Allocation Method of Integrated Energy System Considering Joint Operation of Multiple Flexible Resources by DENG Qianwen, LI Qi, QIU Yibin, LI Doumeng, HUO Shasha, CHEN Weirong

“…Then, aimed at the uncertainty of renewable energy output, the optimal clustering number is determined by Elbow method, and typical wind speed scenarios are obtained by K-means clustering algorithm. …”
Get full text

Collaborative Optimization of Model Pruning and Knowledge Distillation for Efficient and Lightweight Multi-Behavior Recognition in Piglets by Yizhi Luo, Kai Lin, Zixuan Xiao, Yuankai Chen, Chen Yang, Deqin Xiao

“…In the first stage, the LAMP pruning algorithm is used to prune and optimize redundant channels, resulting in the lightweight YOLOv8-Prune. …”
Get full text

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

“…Given the increased risk for AD and health care barriers among rural-residing older adults, tailoring interventions to align with rural culture and distinct needs is important to improve accessibility and adherence. ObjectiveThis protocol aims to develop an intelligent recommendation system capable of identifying the optimal therapeutic music components to elicit engagement and resonate with diverse rural-residing older adults at risk for AD. …”
Get full text

Application of CycleGAN-based low-light image enhancement algorithm in foreign object detection on belt conveyors in underground mines by Anxin Zhao, Qiuhong Zheng, Liang Li

“…To address this issue, an improved CycleGAN-based low-illumination image enhancement algorithm is proposed, which employs a cycle generative adversarial network for unsupervised learning. …”
Get full text

Ecological and Statistical Evaluation of Genetic Algorithm (GARP), Maximum Entropy Method, and Logistic Regression in Predicting Spatial Distribution of Astragalus sp. by Amir Ghahremanian, Abbas Ahmadi, Hamid Toranjzar, Javad Varvani, Nourollah Abdi

“…This study aims to evaluate the potential habitat of Astragalus sp. using three different species distribution modeling methods: the maximum entropy (MaxEnt) model, the Genetic Algorithm for Rule-Set Production (GARP), and logistic regression. …”
Get full text

Algorithms for the treatment of patients with chronic cerebral ischemia of stages I and II with use of Picamilon: results of an open clinical comparative study by Andrei B. Danilov, Natalia N. Shindryaeva, Irina V. Borodulina, Timothy D. Lunegov

Get full text

Model order reduction of boiler system using nature-inspired metaheuristic optimization of PID controller by Anurag Singh, Shekhar Yadav, Nitesh Tiwari, Dinesh Kumar Nishad, Saifullah Khalid

“…The HHO-based approach improves overall performance by 15%, while SSO significantly reduces computational complexity by 65% while maintaining 98% system accuracy. …”
Get full text

Process Optimization for Complex Product Assembly Workshops with AGV Integration via Discrete Event Simulation by Hailong Song, Shengluo Yang, Shuoxin Yin, Zhigang Xu

“…This model simulates the coordination between AGVs and workstations while optimizing workstation layout and material flow. …”
Get full text

AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…In this study, we develop an integrated framework combining conditional generative adversarial networks (cGANs) and deep Q-networks (DQNs) to predict and optimize the stress fields of 2D-PHS. We generated a comprehensive dataet comprising 1000 samples across five distinct density classes using a custom grid pattern generation algorithm, ensuring a wide range of structural variations. …”
Get full text