Distribution network fault comprehensive identification method based on voltage–ampere curves and deep ensemble learning by Jian Wang, Bo Zhang, Dong Yin, Jinxin Ouyang

“…To identify and locate faults of small-current grounded distribution networks under high-impedance fault with weak characteristics, a fault comprehensive identification method for distribution networks based on voltage-ampere curves and deep ensemble learning is proposed. First, the correlations of the voltage-ampere curves with the fault causes, fault types, and fault distances are analyzed to illustrate the feasibility of using three-phase and zero-sequence voltage-ampere curves as input features. …”
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Predicting ixodid tick distribution in Tamil Nadu domestic mammals using ensemble species distribution models by Ayyanar Elango, Hari Kishan Raju, Ananganallur Nagarajan Shriram, Ashwani Kumar, Manju Rahi

“…The present study adopts the package ‘SSDM’ (stacked species distribution models) with R software containing ensemble species distribution models to predict the distribution of tick species using different available environmental and climatic data. …”
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Marcher ensemble : expérience dans le paysage, de la spatialité à l’expérience commune by Ekaterina Shamova

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A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method by Ankit Kumar, Kamred Udham Singh, Manish Kumar

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Structured Clanning-Based Ensemble Optimization Algorithm: A Novel Approach for Solving Complex Numerical Problems by Avinash Sharma, Rajesh Kumar, Akash Saxena, B. K. Panigrahi

“…In this paper, a novel swarm intelligence-based ensemble metaheuristic optimization algorithm, called Structured Clanning-based Ensemble Optimization, is proposed for solving complex numerical optimization problems. …”
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State of Charge Estimation for Lithium-Ion Battery via MILS Algorithm Based on Ensemble Kalman Filter by Quanchun Yan, Kangkang Yuan, Wen Gu, Chenlong Li, Guoqiang Sun, Yanan Liu

“…This paper presents an ensemble Kalman filter- (EnKF-) based SOC estimation algorithm for lithium-ion battery. …”
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An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection by Mohd Sakib, Tamanna Siddiqui, Suhel Mustajab, Reemiah Muneer Alotaibi, Nouf Mohammad Alshareef, Mohammad Zunnun Khan

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Skillful subseasonal ensemble predictions of heat wave onsets through better representation of land surface uncertainties by Qiyu Zhang, Mu Mu, Guodong Sun

“…A better representation of the uncertainties in land surface processes using ensemble prediction methods may be an important way to improve HW onset predictions. …”
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GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images by Sonam Aggarwal, Isha Gupta, Ashok Kumar, Sandeep Kautish, Abdulaziz S. Almazyad, Ali Wagdy Mohamed, Frank Werner, Mohammad Shokouhifar

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A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

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Fully Connected Neural Networks Ensemble with Signal Strength Clustering for Indoor Localization in Wireless Sensor Networks by Marcin Bernas, Bartłomiej Płaczek

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A Fully Automated Adjustment of Ensemble Methods in Machine Learning for Modeling Complex Real Estate Systems by José-Luis Alfaro-Navarro, Emilio L. Cano, Esteban Alfaro-Cortés, Noelia García, Matías Gámez, Beatriz Larraz

“…Real estate property prices in 433 municipalities are estimated from a sample of 790,631 dwellings, using different ensemble methods based on decision trees such as bagging, boosting, and random forest. …”
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A New Transfer Learning Ensemble Model with New Training Methods for Gear Wear Particle Recognition by Chunhua Zhao, zhangwen Lin, Jinling Tan, Hengxing Hu, Qian Li

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A Comparison Study on Rule Extraction from Neural Network Ensembles, Boosted Shallow Trees, and SVMs by Guido Bologna, Yoichi Hayashi

“…The DIMLP architecture allowed us to produce rules from DIMLP ensembles, boosted shallow trees (BSTs), and Support Vector Machines (SVM). …”
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Ensemble Classification Model With CFS-IGWO–Based Feature Selection for Cancer Detection Using Microarray Data by Pinakshi Panda, Sukant Kishoro Bisoy, Sandeep Kautish, Reyaz Ahmad, Asma Irshad, Nadeem Sarwar

“…Our result shows that majority voting achieves better performance than the weighted average ensemble technique.…”
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Advanced sleep disorder detection using multi-layered ensemble learning and advanced data balancing techniques by Muhammad Mostafa Monowar, S. M. Nuruzzaman Nobel, Maharin Afroj, Md Abdul Hamid, Md Zia Uddin, Md Mohsin Kabir, M. F. Mridha

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Advanced Fraud Detection: Leveraging K-SMOTEENN and Stacking Ensemble to Tackle Data Imbalance and Extract Insights by Nurafni Damanik, Chuan-Ming Liu

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A New Decomposition Ensemble Learning Approach with Intelligent Optimization for PM2.5 Concentration Forecasting by Guangyuan Xing, Shaolong Sun, Jue Guo

“…This decomposition ensemble learning approach mainly consists of three steps. …”
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Network Intrusion Detection and Prevention System Using Hybrid Machine Learning with Supervised Ensemble Stacking Model by Godfrey A. Mills, Daniel K. Acquah, Robert A. Sowah

“…In this paper, we present a hybrid intrusion detection system that combines supervised and unsupervised learning models through an ensemble stacking model to increase the detection accuracy rates of attacks in networks while minimising false alarms. …”
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