Simulation and Prediction of Springback in Sheet Metal Bending Process Based on Embedded Control System by Jinhan Xu, Jun Yan, Yan Huang, Dawei Ding

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A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

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Slope stability prediction under seismic loading based on the EO-LightGBM algorithm by Ning Ma, Ning Ma, Yuqi Zhang, Zaizhen Yao

“…This study proposes an optimized prediction model based on EO-LightGBM to enhance the accuracy of slope stability assessment. …”
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Epidemiological association and machine learning-based prediction of lung cancer risk linked to long-term lagged satellite-derived PM2.5 in China by Feiran Wei, Shijun Yang, Huiying Wang, Meng Zhao, Meng Zhao, Jinyi Zhou, Xiaobing Shen, Xiaobing Shen, Renqiang Han, Renqiang Han, Gaoqiang Fei

“…The integrated machine learning prediction model can be used as a reliable tool to assess the health risks of air pollution.…”
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TextNeX: Text Network of eXperts for Robust Text Classification—Case Study on Machine-Generated-Text Detection by Emmanuel Pintelas, Athanasios Koursaris, Ioannis E. Livieris, Vasilis Tampakas

“…The development process of TextNeX model follows a three-phase procedure: (i) <i>Expansion</i>: generation of a pool of diverse lightweight models via randomized model setups and variations of training data; (ii) <i>Selection</i>: application of a clustering-based heterogeneity-driven selection to retain the most complementary models and (iii) <i>Ensemble optimization</i>: optimization of the selected models’ contributions using sequential quadratic programming. …”
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Enhancing landslide dam stability prediction: a data-driven framework integrating missing data imputation and optimal threshold discrimination by Xiaojun Li, Xiaobo Zhang, Jun He, Yixiang Song, Yanqi Li

“…Imputed datasets were used to train four ML models (SVM, RF, XGBoost, LR), with GAIN-SVM further optimized via Youden-index-based threshold discrimination.ResultsGAIN achieved the lowest RMSE (0.205) for continuous variables and 66.0% accuracy for categorical data. …”
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Highway Rest Area Truck Parking Occupancy Prediction Using Machine Learning: A Case Study from Poland by Artur Budzyński, Maria Cieśla

“…Eight classification models—Gradient Boosting, XGBoost, Random Forest, k-NN, Decision Tree, Logistic Regression, SVM, and Naive Bayes—were implemented and compared using standard performance metrics. …”
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Explainable machine learning for predicting distant metastases in renal cell carcinoma patients: a population-based retrospective study by Zhao Hou, Zhao Hou, Peipei Wang, Peipei Wang, Dingyang Lv, Dingyang Lv, Huiyu Zhou, Huiyu Zhou, Zhiwei Guo, Zhiwei Guo, Jinshuai Li, Jinshuai Li, Mohan Jia, Mohan Jia, Hongyang Du, Hongyang Du, Weibing Shuang, Weibing Shuang

“…This study aimed to establish and validate a clinical prediction model for distant metastasis in RCC patients.MethodsTen machine learning algorithms were employed to develop a predictive model for distant metastasis in RCC. …”
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Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms by DENG Zhiyu, CUI Dongwen

“…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection by Majid Joudaki, Mehdi Imani, Hamid R. Arabnia

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Data enrichment for semantic segmentation of point clouds for the generation of geometric-semantic road models by David Crampen, Joerg Blankenbach

“…This workflow is adaptable to various model architectures, from deep learning methods like PointNet++ and PointNeXt to traditional machine learning models such as Random Forest. …”
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System Development for Liquid Chemicals Point Injection Based on Convolutional Neural Network Models by V. S. Semenyuk, E. A. Nikitin

“…(Research purpose) To develop a system of liquid chemicals point application for plant protection and nutrition based on a convolutional neural network model. (Materials and methods) The authors analyzed the existing methods of machine learning. …”
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Explainable Climate-Based Time Series Modeling for Predicting Chemical Compositions in Tobacco Leaves by Hong He, Yunwei Zhang, Bin Li, Chengjin Tao

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Winter Wheat Nitrogen Content Prediction and Transferability of Models Based on UAV Image Features by Jing Zhang, Gong Cheng, Shaohui Huang, Junfang Yang, Yunma Yang, Suli Xing, Jingxia Wang, Huimin Yang, Haoliang Nie, Wenfang Yang, Kang Yu, Liangliang Jia

“…While multispectral unmanned aerial vehicle (UAV) imagery has shown promise in PNC estimation, the optimal feature combination methods of spectral and texture features remain underexplored, and model transferability across different agricultural practices is poorly understood. …”
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Population-based colorectal cancer risk prediction using a SHAP-enhanced LightGBM model by Guinian Du, Hui Lv, Yishan Liang, Jingyue Zhang, Qiaoling Huang, Guiming Xie, Xian Wu, Hao Zeng, Lijuan Wu, Jianbo Ye, Wentan Xie, Xia Li, Yifan Sun

“…Seven ML algorithms were systematically compared, with Light Gradient Boosting Machine (LightGBM) ultimately selected as the optimal framework. …”
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Behavioral Study of Bayesian Neural Networks Under a Typical Surrogate Model-Assisted Evolutionary Search Framework by Yushi Liu, Muhammad Ali Imran, Masood Ur-Rehman, Bo Liu

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A CART-Based Model for Analyzing the Shear Behaviors of Frozen–Thawed Silty Clay and Structure Interface by Fengpan Zhu, Bo Wang, Zhiqiang Liu

“…The physical and mechanical properties of the soil–structure interface under the freeze–thaw condition are complex, making empirical shear strength models poorly applicable. This study employs integrated machine learning algorithms to model the shear behavior of frozen–thawed silty clay and the structure interface. …”
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A multi-algorithm prognostic model combining inflammatory indices and surgical features in distal cholangiocarcinoma by Yi Yin, Yi Yin, Luyuan Bai, Xinyue Mu, Xinyue Mu, Shan Zhang, Panpan Zhai, Panpan Zhai

“…The clinical prediction model based on machine learning incorporating dNLR effectively predicts postoperative outcomes in this patient population.…”
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Ensemble modeling of the climate-energy nexus for renewable energy generation across multiple US states by Joy Adul, Rohini Kumar, Renee Obringer

“…We analyze data from four key states: California, New York, Florida, and Georgia, and focus on three critical renewable energy sources: hydroelectric, solar, and wind power. To determine the optimal model, we test six primary machine learning techniques, as well as an ensemble and a mean-only baseline. …”
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AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models by Faruk Dikmen, Ahmet Demir, Bestami Özkaya, Muhammad Owais Raza, Jawad Rasheed, Tunc Asuroglu, Shtwai Alsubai

“…This study evaluates the performance of machine learning models in predicting key wastewater effluent parameters Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS), Total Effluent Nitrogen and Total Effluent Phosphorus. …”
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