Economic sizing and placement of hydrogen fueling and electric vehicles charging stations powered by renewable and battery systems in smart distribution network by Mehdi Veisi

“…The solution is derived using Benders decomposition algorithm to achieve optimal results. The primary innovation highlighted in this paper includes integrating renewable resources and battery systems to power the refueling station, leveraging reactive power control for improved station performance, and addressing both operational and economic objectives in the distribution system. …”
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Soil Parameter Inversion in Dredger Fill Strata Using GWO-MLSSVR for Deep Foundation Pit Engineering by Changrui Chen, Sifan Li, Jinbi Ye, Fangjian Chen, Yibin Wu, Jin Yu, Yanyan Cai, Jinna Lin, Xianqi Zhou

“…Compared to traditional inversion methods and MLSSVR models optimized by other algorithms, this approach significantly reduces prediction errors. …”
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A novel multiscale feature enhancement network using learnable density map for red clustered pepper yield estimation by Chenming Cheng, Chenming Cheng, Jin Lei, Jin Lei, Zicui Zhu, Lijian Lu, Lijian Lu, Zhi Wang, Zhi Wang, Jiali Tao, Jiali Tao, Xinyan Qin, Xinyan Qin

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Optimization Allocation of Resources for Massive Manufacturing Service Requests by ZHANG Hong-guo, SHI Yan-lei, MA Chao, ZHANG Shu-li, LIU Sheng-hui

“…Then the correlated region is constructed under the premise of ensuring the integrity of manufacturing service request. …”
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Parameter identification of unmanned surface vehicle MMG model based on an improved extended Kalman filter by Pengbo SUN, Zaopeng DONG, Wei LIU, Jinliang SHENG, Zhihao LI

“…ObjectivesTo construct an accurate MMG （mathematical model group） model for a water-jet propulsion unmanned surface vehicle, the traditional extended Kalman filter algorithm and improved extended Kalman filter algorithm are combined with the real-world boat data for parameter identification. …”
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Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…The sliding window that constructs observation and reference vectors is established, which effectively avoids the accumulation of sensor errors during the full integration process. …”
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Research on predicting the risk level of coal mine roof accident based on machine learning by Zhao-Yang Guan, Jin-Ling Xie, Shen-Kuang Wu, Chao Liang

“…Through comparison of model performance evaluation metrics, the Random Forest integration algorithm is introduced to improve the evaluation and prediction of the model, and the prediction accuracy jumps to 0.94. …”
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Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China by Jinze Li, Xiao Wang, Qiyan Zhang, Peng Tang

“…A multi-objective evolutionary algorithm calculates Pareto optimal solutions for site selection, allowing for a balanced consideration of conflicting EMS siting objectives. …”
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Optimization and Benefit Assessment of LID Layout Based on the MCDA Approach at a Campus Scale by Zexin Lei, Lijun Li, Yanrou Wei, Wenzheng Zhang, Junjie Luo, Xuqiang Zhao

“…This study evaluates four representative LID types—green roofs, sunken green spaces, permeable pavement, and rain gardens—using an integrated framework combining the Storm Water Management Model (SWMM), NSGA-II genetic algorithm, and Analytic Hierarchy Process (AHP) at Taiyuan University of Technology in Shanxi Province, China. …”
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TBM Enclosure Rock Grade Prediction Method Based on Multi-Source Feature Fusion by Yong Huang, Xiewen Hu, Shilong Pang, Wei Fu, Shuaipeng Chang, Bin Gao, Weihua Hua

“…In the data preprocessing stage, the TBM data is cleaned and divided according to the mileage section, the statistical characteristics of key tunnelling parameters (thrust, torque, penetration, etc.) are extracted, and the rock fragmentation index (TPI, FPI, WR) is fused to construct a composite feature vector. The Direct-LiNGAM causal discovery algorithm is innovatively introduced to analyse the nonlinear correlation mechanism between multi-source features, and then a hybrid model, TRNet, which combines the local feature extraction ability of convolutional neural networks and the nonlinear approximation advantages of Kolmogorov–Arnold networks, is constructed. …”
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Large language models in the management of chronic ocular diseases: a scoping review by Jiatong Zhang, Xiaoxi Song, Bocheng Tian, Mingke Tian, Zhichang Zhang, Jing Wang, Ting Fan

“…Future directions emphasize the need for specialized model training, multimodal algorithm optimization, the establishment of a multinational multicenter clinical validation platform, and the construction of an ethical framework for dynamic regulation. …”
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Optimal Autonomous Control for Distribution Transformer Area With High Photovoltaic Penetration Based on CSBO-LSTM by Yukai Wei, Chun He, Zhuo Chen, Yinyuan Guo, Zongyuan Li

“…To enhance the autonomous control capability of transformer area with high PV penetration, this paper proposes a “data-model” dual-driven collaborative optimization model that integrates the Circulatory System Based Optimization (CSBO) algorithm and Long Short-Term Memory (LSTM), constructing an architecture of “offline optimization-knowledge migration-online inference”. …”
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Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

“…To accurately and efficiently predict the stability state of slopes, we propose a combined model that integrates the Newton–Raphson optimization algorithm (NRBO) with an optimized extreme gradient boosting tree (XGBoost). …”
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Viewpoint Selection for 3D Scenes in Map Narratives by Shichuan Liu, Yong Wang, Qing Tang, Yaoyao Han

“…Pearson’s correlation coefficient is used to evaluate the relationship between visual salience and narrative relevance, serving as a constraint to construct a viewpoint fitness function that integrates the visual salience of the convex polyhedron enclosing the scene. …”
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Rapid and Accurate Measurement of Major Soybean Components Using Near-Infrared Spectroscopy by Chenxiao Li, Jiatong Yu, Sheng Wang, Qinglong Zhao, Qian Song, Yanlei Xu

“…Feature selection was conducted using competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), and uninformative variable elimination (UVE), followed by model construction with partial least squares regression (PLSR), support vector regression (SVR), and random forest (RF). …”
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Damage Identification of Conduit Rack in Offshore Platform Structures Based on a Novel Composite Neural Network by Jiaqiang Yan, Yuanchao Qiu, Renhe Shao, Ziqiao Ling, Ruixiang Zhang

“…In addition, we adopt the Newton-Raphson-based optimiser (NRBO) optimisation algorithm for global optimisation of the hyperparameters of TCN and BiLSTM to avoid the subjectivity of manual parameter tuning, which significantly improves the model convergence speed and generalisation performance. …”
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Explainable artificial intelligence to estimate the Sri Lankan (Ceylon) Tea crop yield by Lakindu Mampitiya, Harindu S. Sumanasekara, Namal Rathnayake, Yukinobu Hoshino, Upaka Rathnayake

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Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model. by Yongxin Dai, Zijian Li, Jingbiao Lu

“…This paper proposes a comprehensive technical system for landslide early hazard warning in open-pit mine slopes, encompassing the full process of monitoring data acquisition and processing, analysis of influencing mechanisms, intelligent algorithm-based prediction, and the construction of early hazard warning indicators. …”
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Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…Finally, we construct the U-FRQL-EA equalization algorithm by combining the improved U-Net model with fuzzy reinforcement Q-learning. …”
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Application of hyperthermia robots in Cyber-syndrome treatment by Xueyan YIN, Feifei SHI, Jinqiang WANG, Huansheng NING

“…Traditional technologies are now integrated with artificial intelligence techniques, such as big data analysis and visualization algorithms, enabling more precise and personalized treatment services that effectively alleviate the symptoms of Cyber-syndrome. …”
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