An enhanced approach for automatic annotation of error codes based on Seq2edit by Jian Wang, Tao Lin, Rongsen Zhao, Huiling Zhao

“…By dividing the code into statements with independent meanings and introducing a cost coefficient to improve the Levenshtein algorithm, this method optimizes the calculation of edit distance and enhances the ability to align tokens. …”
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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…Additionally, an iterative optimization search is performed to determine the final optimal feature subset, thus deriving the auxiliary variable set for modeling. …”
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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…Thirdly, large language models will enhance human-robot interaction by enabling natural language commands, improving collaborative operations. …”
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Power supply vehicle routing problem: formulation and solution by Lizhe You, Shengjun Huang, Haowei Zhang, Rui Wang, Tao Zhang

“…Building on this definition, this problem is formulated as a two-stage mixed-integer nonlinear programming model. To solve this model, we adopted a genetic algorithm as the main algorithm framework. …”
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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…Additionally, the Decision Tree (DT), Random Forest (RF), k-Nearest Neighbors (kNN), and GRU classification algorithms are also evaluated and compared with the XGBoost and LSTM classifiers for the proposed attack model. …”
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A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices by Hui Xiang, Xiao Liao, Yanjie Wang, Hui Cao, Xianjing Zhong, Qingshu Guan, Weiyun Ru

“…A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. …”
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Intelligent Wireless Power Scheduling for Lunar Multienergy Systems: Deep Reinforcement Learning for Real-Time Adaptive Beam Steering and Vehicle-to-Grid Energy Optimization by Thomas Tongxin Li, Shuangqi Li, Cynthia Xin Ding, Zhaoyao Bao, Mohannad Alhazmi

“…The results validate the feasibility of DRL–based WPT control, paving the way for scalable, resilient, and self-optimizing wireless power grids on the Moon. Future work will explore the integration of hybrid energy storage models, quantum-inspired optimization for real-time decision-making, and predictive beamforming algorithms to further enhance the reliability and efficiency of lunar energy networks.…”
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A Novel Reactive Power Sharing Control Strategy for Shipboard Microgrids Based on Deep Reinforcement Learning by Wangyang Li, Hong Zhao, Jingwei Zhu, Tiankai Yang

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A Decomposed-Ensemble Prediction Framework for Gate-In Operations at Container Terminals by Yifan Shen, Beng Xuan, Hongtao Hu, Yansong Wu, Ning Zhao, Zhen Yang

“…The experiment compares the autoregressive integrated moving average (ARIMA) algorithm, the prophet algorithm, and the Long Short-Term Memory (LSTM) algorithm, with results indicating the clear advantage of Long Short-Term Memory in decomposed time series modeling. …”
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The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat by Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, Md. Nurealam Siddiqui, Mohammad Kamruzzaman, Ahossi Patrice Koua, Jens Léon

“…By incorporating the neural network algorithm, it is possible to improve the reliability of FDR threshold and increase the probability of identifying true genetic associations while minimizing the risk of false positives in GWAS results.…”
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Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification by Zuojun Zheng, Jianghao Yuan, Wei Yao, Paul Kwan, Hongxun Yao, Qingzhi Liu, Leifeng Guo

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The ADBPSO-LightGBM internal threat detection framework based on hybrid data balancing by Jin-Jie Zheng, Xiu Kan, Jian-Zhen Wu, Zhen Zhang, Xiu-Yu Gao

“…Moreover, to further construct the behaviour model, an improved particle swarm optimization algorithm based on adaptive delay and genetic factors is proposed, and it is used to search for the optimal parameters of LightGBM. …”
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METHOD FOR MODIFYING PROFILE OF CYCLOIDAL WHEEL CONSIDERING COMPENSATION FOR ELASTIC DEFORMATION by QIN ZhengZheng, WANG Quan, ZHAO DaXing, WANG Jun, ZENG LiLei

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Vehicle routing problem in waste collection: a case study in Son Tra, Da Nang by Le Hoang Son, Truong Nguyen Song Ha, Nguyen Ngoc Phuong, Phan Bao An

“…By employing the Dijkstra algorithm, route optimization resulted in a significant reduction in average route length, from 12.94 ± 3.5 km to 9.42 ± 2.67 km, representing a 9-42% improvement. …”
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Enhancing Extreme Learning Machine Robustness via Residual-Variance-Aware Dynamic Weighting and Broyden–Fletcher–Goldfarb–Shanno Optimization: Application to Metro Crowd Flow Predi... by Lihui Wang, Jianguang Xie

“…Aiming at the robustness problem of the extreme learning machine (ELM) in noisy and nonuniform data scenarios, this paper proposes an improved algorithm (BFGS-URWELM) that integrates uniform residual weighting and Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton optimization. …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…Among these models, the Random Forest-based model exhibited lower mean squared error and a higher coefficient of determination, outperforming the XGBoost-based model. …”
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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…In addition, the Cross-Validation Grid Search Algorithm (GSA) was used to optimize the hyperparameters to ensure that the model can achieve the optimal performance on different data sets. …”
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Data-driven seismic mechanical performance evaluation of RC columns based on adaptive optimization ensemble learning method integrating random forest and back propagation neural ne... by Ayong Jiao, Ziqing Jiao, Bin Gao

“…An improved black-winged kite optimization algorithm (IBKA), based on Levy flight and adaptive t-distribution strategies, is used to optimize the hyperparameters of the base models. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Coupling HEC-RAS and AI for River Morphodynamics Assessment Under Changing Flow Regimes: Enhancing Disaster Preparedness for the Ottawa River by Mohammad Uzair Anwar Qureshi, Afshin Amiri, Isa Ebtehaj, Silvio José Guimere, Juraj Cunderlik, Hossein Bonakdari

“…Despite significant advancements in flood forecasting using machine learning (ML) algorithms, recent events have revealed hydrological behaviors deviating from historical model development trends. …”
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