A machine learning-based predictive model for the occurrence of lower extremity deep vein thrombosis after laparoscopic surgery in abdominal surgery by Su-Zhen Yang, Ming-Hui Peng, Quan Lin, Shi-Wei Guan, Kai-Lun Zhang, Hai-Bo Yu

“…Twenty machine learning algorithms were evaluated, and the top five algorithms were used to build the final model by stacking.ResultsA total of 335 patients underwent laparoscopic abdominal surgery. …”
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Matching of Observation Footprints in the FY-3G MWRI-RM Using BGI by Ke Chen, Bowen Cai, Wei Han, Zihao Suo

“…The remapping results of real observations demonstrate that our algorithm effectively suppresses noise in each channel.…”
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Ensemble Learning-Driven and UAV Multispectral Analysis for Estimating the Leaf Nitrogen Content in Winter Wheat by Yu Han, Jiaxue Zhang, Yan Bai, Zihao Liang, Xinhui Guo, Yu Zhao, Meichen Feng, Lujie Xiao, Xiaoyan Song, Meijun Zhang, Wude Yang, Guangxin Li, Sha Yang, Xingxing Qiao, Chao Wang

“…Support Vector Regression (SVR), Random Forest (RF), Ridge Regression (RR), K-Nearest Neighbors (K-NN), and ensemble learning algorithms (Voting and Stacking) were employed to model the relationship between selected vegetation indices and LNC. …”
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Efficient Machine Learning Models for Solar Radiation Prediction Using Ensemble Techniques: A Case Study in Low-Rainfall Arid Climates by Jimmy Aurelio Rosales Huamani, Uwe Rojas Villanueva, Christian Leonardo Rosales Ventocilla, Jose Luis Castillo Sequera, Jose Manuel Gomez Pulido

“…Finally, ensemble techniques were applied to enhance prediction accuracy by combining various ML algorithms. The best results were obtained using the Stacking Regressor (SR), achieving an <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> of 0.92, RMSE of 47.30 W/<inline-formula> <tex-math notation="LaTeX">$m^{2}$ </tex-math></inline-formula>, and MAE of 18.27 W/<inline-formula> <tex-math notation="LaTeX">$m^{2}$ </tex-math></inline-formula>, demonstrating high predictive performance in the target climate region.…”
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A Routing Scheme for IPv6-Based All-IP Wireless Sensor Networks by Wang Xiaonan, Zhong Shan

“…The paper creates the IPv6 address structure and the IPv6 address configuration algorithm for all-IP wireless sensor networks. Based on the IPv6 address structure, the paper proposes the routing algorithm in the link layer for all-IP wireless sensor networks. …”
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Blockchain-Enabled Deep Recurrent Neural Network Model for Clickbait Detection by Abdul Razaque, Bandar Alotaibi, Munif Alotaibi, Fathi Amsaad, Ansagan Manasov, Salim Hariri, Banu B. Yergaliyeva, Aziz Alotaibi

“…The scammer attempts to create a striking headline that attracts the majority of users and attaches a link. …”
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Data analytics approach for short- and long-term mortality prediction following acute non-ST-elevation myocardial infarction (NSTEMI) and Unstable Angina (UA) in Asians. by Sazzli Kasim, Putri Nur Fatin Amir Rudin, Sorayya Malek, Firdaus Aziz, Wan Azman Wan Ahmad, Khairul Shafiq Ibrahim, Muhammad Hanis Muhmad Hamidi, Raja Ezman Raja Shariff, Alan Yean Yip Fong, Cheen Song

“…In the development of the stacked EL model, four base learner algorithms were employed: eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF), with the Generalized Linear Model (GLM) serving as the meta learner. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Finally, the pre-dicted values of each subsequence are sequentially stacked to obtain the result, which is expected to provide reliable predictions for wind power generation.Results and DiscussionsThe RF algorithm is strategically employed to screen meteorological features and systematically rank their importance, enabling the accurate selection of features that significantly impact wind power forecasting. …”
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USING THE KARHUNEN-LOÈVE TRANSFORM TO SUPPRESS GROUND ROLL IN SEISMIC DATA by Kazmierczak Thaís de Souza, Castillo López Luís, Gómez Londoño Ernesto

“…ABSTRACTThe Sacchi's algorithm (2002) based on the Karhunen-Loève (K-L) Transform was modified and implemented to suppress Ground Roll without distortion of the reflection signals, it provided better results than conventional techniques for noise removal like f-k, High-Pass and Band Pass Filters. …”
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Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections by Oona Rainio, Heidi Huhtanen, Jari-Pekka Vierula, Janne Nurminen, Jaakko Heikkinen, Mikko Nyman, Riku Klén, Jussi Hirvonen

“…First, a convolutional neural network (CNN) classified individual slices; second, an algorithm classified patients based on a stack of slices. …”
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Multi-Camera Machine Learning for Salt Marsh Species Classification and Mapping by Marco Moreno, Sagar Dalai, Grace Cott, Ben Bartlett, Matheus Santos, Tom Dorian, James Riordan, Chris McGonigle, Fabio Sacchetti, Gerard Dooly

“…UAV surveys were conducted with RGB, MSI, and HSI sensors, and the collected data were classified using Random Forest (RF), Spectral Angle Mapper (SAM), and Support Vector Machine (SVM) algorithms. The classification performance was assessed using Overall Accuracy (<i>OA</i>), Kappa Coefficient (<i>k</i>), Producer’s Accuracy (<i>PA</i>), and User’s Accuracy (<i>UA</i>), for both individual sensor datasets and the fused dataset generated via band stacking. …”
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GPC-YOLO: An Improved Lightweight YOLOv8n Network for the Detection of Tomato Maturity in Unstructured Natural Environments by Yaolin Dong, Jinwei Qiao, Na Liu, Yunze He, Shuzan Li, Xucai Hu, Chengyan Yu, Chengyu Zhang

“…Current deep learning detection algorithms typically demand significant computational resources and memory. …”
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Learning Improvement Heuristics for Multi-Unmanned Aerial Vehicle Task Allocation by Boyang Fan, Yuming Bo, Xiang Wu

“…Nowadays, small UAV swarms with the capability of carrying inexpensive munitions have been highly effective in strike missions against ground targets on the battlefield. …”
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Machine learning prediction of permeability distribution in the X field Malay Basin using elastic properties by Zaky Ahmad Riyadi, John Oluwadamilola Olutoki, Maman Hermana, Abdul Halim Abdul Latif, Ida Bagus Suananda Yogi, Said Jadid A. Kadir

“…Several ensemble-based models, including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LightBoost), Categorical Gradient Boosting (CatBoost), Bagging Regressor, Random Forest and Stacking, were evaluated for predictive performance, along with Multi-Layered Perceptron Neural Network algorithms. …”
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Predicting cardiotoxicity in drug development: A deep learning approach by Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han

“…We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. …”
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Application of ANFIS Technique for Wide-Band Modeling of Overvoltage of Single-Conductor Overhead Lines with Arrester above Dispersive and Two-Layer Soils by Saeed Reza Ostadzadeh

“…In this paper, an efficient closed-form expression for overvoltage of overhead lines under direct strike in the presence of lightning arresters is presented. …”
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Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

“…Notably, this surpasses the capabilities of other models that rely on amalgamations of machine learning algorithms and feature dimensionality reduction methods. …”
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Real time obstacle motion prediction using neural network based extended Kalman filter for robot path planning by Najva Hassan, Abdul Saleem P.K

“…In terms of computation time and robustness in closely spaced obstacles, simulation experiments demonstrated that the path planning using the proposed algorithm outperforms the hybrid A star, artificial potential field, and decision algorithms. …”
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Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems by Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Satyesh Shanker Awasthi, Michael Khayyat, Stefano Arrigoni, Francesco Braghin

“…In the context of increasing research on algorithms for different modules of the autonomous driving stack, the development and evaluation of these algorithms for deployment onboard vehicles is the next critical step. …”
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Intelligent Online Multiconstrained Reentry Guidance Based on Hindsight Experience Replay by Qingji Jiang, Xiaogang Wang, Yuliang Bai, Yu Li

“…Traditional guidance algorithms for hypersonic glide vehicles face the challenge of real-time requirements and robustness to multiple deviations or tasks. …”
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