A Full-Profile Measurement Method for an Inner Wall with Narrow-Aperture and Large-Cavity Parts Based on Line-Structured Light Rotary Scanning by Zhengwen Li, Changshuai Fang, Xiaodong Zhang

“…Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. …”
Get full text

Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks by Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai

“…To achieve this goal, we formulate the model partitioning problem among heterogeneous hardware and introduce a hierarchical searching algorithm to solve the optimization problem. Besides, a mixed-precision pipeline method is used to reduce the cost of inter-cluster communications. …”
Get full text

Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
Get full text

Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). …”
Get full text

Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
Get full text

Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

“…By evaluating performance of several regression algorithms using various metrics, this study identifies the most effective method for analyzing sectoral energy consumption. …”
Get full text

Threat analysis model to control IoT network routing attacks through deep learning approach by K. Janani, S. Ramamoorthy

“…A deep learning hybrid model based on a Long-Short-Term Memory (LSTM) network and adaptive Mayfly Optimization Algorithm (LAMOA) was presented for the classification of IoT attacks. …”
Get full text

Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

Get full text

Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

“…Finally, the proposed algorithm is applied to a post-disaster rescue scenario, where the task allocation results further demonstrate its superior performance.…”
Get full text

Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…The results underscore the potential of ML models to significantly enhance prediction accuracy over a wide data range, reduce computational costs, and improve the efficiency of CCUS operations. …”
Get full text

Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning by Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu

“…However, the hyperparameters of the deep learning, which significantly impact the feature extraction and prediction performance, are determined based on expert experience in most cases. The grid search method is introduced in this paper to optimize the hyperparameters of the proposed aircraft engine RUL prediction model. …”
Get full text

Research on Control System for Material Transport Vehicle Based on Stacking Model by LIU Yuanming, TANG Lingsi, Zen Shuhua

“…Finally, the control system was reinforced using an improved proportional-integral-differential (PID) control algorithm to optimize the control performance. …”
Get full text

Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…Additionally, a custom ranking algorithm was designed to identify the most suitable recipients. …”
Get full text

Battery swapping scheduling for electric vehicles: a non-cooperative game approach by Yu Zhang, Tao Han, Wei He, Jianhua Xia, Lichao Cui, Zuofu Ma, Shiwei Liu

“…Therefore, it is crucial to develop efficient battery-swapping scheduling algorithms to optimize the operations of battery-swapping systems. …”
Get full text

A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD by Fengfeng Bie, Xueping Ding, Qianqian Li, Yuting Zhang, Xinyue Huang

“…Initially, the critical parameters (modal number n and filter length L) of FMD are optimized using an improved genetic algorithm (IGA), and the refined FMD is employed to decompose the vibration signals from the planetary gearbox. …”
Get full text

GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…Enhanced by local mean optimization and adaptive noise regulation, the ICEEMDAN algorithm effectively suppresses pseudo-modes and minimizes residual noise, enabling its decomposed intrinsic mode functions (IMFs) to more accurately capture the multi-scale features of GNSS-PWV. …”
Get full text

Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations by Min-Hwa Choi, Woongchang Yoon

“…The XGBoost Regressor (XGBR) is optimized using genetic-algorithm-based hyperparameter tuning, reducing mean squared error (RMSE) from 20.9531 to 19.6387, mean absolute error (MAE) from 13.6821 to 12.6753, and improving coefficient of determination (R2) from 0.2791 to 0.2949. …”
Get full text

Modern aspects of diagnosis and treatment of patients with spontaneous coronary artery dissection by Sh. Sh. Zainobidinov, D. A. Khelimsky, A. A. Baranov, A. G. Badoyan, O. V. Krestyaninov

“…The angiographic classification of SCAD, the diagnostic algorithm and the choice of optimal treatment depending on clinical manifestations are also described.…”
Get full text

IHML: Incremental Heuristic Meta-Learner by Onur Karadeli, Kıymet Kaya, Şule Gündüz Öğüdücü

“…Existing work in this context utilizes XAI mostly in pre-processing the data or post-analysis of the results, however, IHML incorporates XAI into the learning process in an iterative manner and improves the prediction performance of the meta-learner. …”
Get full text

A New Routing Protocol for Heterogeneous Mobile Ad Hoc Networks by Bahareh Shafaie, Marjan Kuchaki Rafsanjani

“…Homogeneous Mobile Ad hoc Networks are networks in which all nodes have the same sources and capabilities, and this is in contrast with nature of MANETs because nodes are independent and have different sources, capabilities (such as battery lifetime, bandwidth, transmission range,...) and mobility. In this paper, we improve one of proactive routing protocols named OLSR (Optimized Link State Routing Protocol) so that this protocol becomes appropriate for HMANET and do not lose its capability and scalability. …”
Get full text