Intelligent rockburst level prediction model based on swarm intelligence optimization and multi-strategy learner soft voting hybrid ensemble by Qinghong Wang, Tianxing Ma, Shengqi Yang, Fei Yan, Jiang Zhao

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Forecast Customization System (FOCUS): A Multimodel Ensemble-Based Seasonal Climate Forecasting Tool for the Homogeneous Climate Zones of Myanmar by Itesh Dash, Masahiko Nagai, Indrajit Pal

“…A Multi-Model Ensemble (MME) based seasonal rainfall forecast customization tool called FOCUS was developed for Myanmar in order to provide improved seasonal rainfall forecast to the country. …”
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Enhancing aviation control security through ADS-B injection detection using ensemble meta-learning models with Explainable AI by Vajratiya Vajrobol, Geetika Jain Saxena, Sanjeev Singh, Amit Pundir, Brij B. Gupta, Akshat Gaurav, Kwok Tai Chui

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Ensemble learning to predict short birth interval among reproductive-age women in Ethiopia: evidence from EDHS 2016–2019 by Jenberu Mekurianew Kelkay, Deje Sendek Anteneh, Henok Dessie Wubneh, Abraham Dessie Gessesse, Gebeyehu Fassil Gebeyehu, Kalkidan Kassahun Aweke, Mikiyas Birhanu Ejigu, Mathias Amare Sendeku, Kirubel Adrissie Barkneh, Hasset Girma Demissie, Wubshet D. Negash, Birku Getie Mihret

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Analyses et réflexions à partir du symposium « Éduquer au vivre ensemble ou éduquer à la citoyenneté » by Hélène Marquié-Dubié

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Application of adaptive ensemble neural network method for short-term load forecasting electrical engineering complex of regional electric grid by N. A. Serebryakov

“…A comparative analysis of the accuracy of the short-term load forecasting of electrical engineering complex of regional electric grid obtained using the ensemble neural network method and single neural networks are produced.…”
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A Cloud-Based Optimized Ensemble Model for Risk Prediction of Diabetic Progression—An Azure Machine Learning Perspective by V. K. Daliya, T. K. Ramesh

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The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers by Zeinab Hassani, Najmeh Samadiani

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Pep2TCR: Accurate prediction of CD4 T cell receptor binding specificity through transfer learning and ensemble approach by Kaixuan Diao, Tao Wu, Xiangyu Zhao, Nan Wang, Die Qiu, Wei‐Liang Wang, Xinxiang Li, Xue‐Song Liu

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Comparison of Single and Ensemble Regression Model Workflows for Estimating Basal Area by Tree Size Class in Pine Forests of Southeastern U.S by Joseph St. Peter, Jason Drake, Paul Medley, Eben Broadbent, Gang Chen, Victor Ibeanusi

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Hybrid clustering strategies for effective oversampling and undersampling in multiclass classification by Amirreza Salehi, Majid Khedmati

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Kulturelle Diversität in der empirischen Rhythmusforschung. Drei Analysen eines Audio-Korpus von Percussion-Ensemblemusik aus Mali by Rainer Polak, Nori Jacoby, Justin London

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Combining UAV Remote Sensing with Ensemble Learning to Monitor Leaf Nitrogen Content in Custard Apple (<i>Annona squamosa</i> L.) by Xiangtai Jiang, Lutao Gao, Xingang Xu, Wenbiao Wu, Guijun Yang, Yang Meng, Haikuan Feng, Yafeng Li, Hanyu Xue, Tianen Chen

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Ensemble-based customer churn prediction in banking: a voting classifier approach for improved client retention using demographic and behavioral data by Ruchika Bhuria, Sheifali Gupta, Upinder Kaur, Salil Bharany, Ateeq Ur Rehman, Seada Hussen, Ghanshyam G. Tejani, Pradeep Jangir

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Monitoring Over Time of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients Through an Ensemble Vision Transformers‐Based Model by Maria Colomba Comes, Annarita Fanizzi, Samantha Bove, Luca Boldrini, Agnese Latorre, Deniz Can Guven, Serena Iacovelli, Tiziana Talienti, Alessandro Rizzo, Francesco Alfredo Zito, Raffaella Massafra

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An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

“…This study aims to develop an ensemble machine learning approach to evaluate the performance (rank) of pathogenic and conservation scoring algorithms (PCSAs) based on their ability to distinguish pathogenic driver mutations from benign passenger (non-driver) mutations in head and neck squamous cell carcinoma (HNSC). …”
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A Multivariate and Multistage Medium- and Long-Term Streamflow Prediction Based on an Ensemble of Signal Decomposition Techniques with a Deep Learning Network by Muhammad Sibtain, Xianshan Li, Snoober Saleem

“…Finally, the predicted results of all components were aggregated, to formulate an ensemble prediction for the original monthly streamflow series. …”
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WDRIV-Net: a weighted ensemble transfer learning to improve automatic type stratification of lumbar intervertebral disc bulge, prolapse, and herniation by Ichiro Nakamoto, Hua Chen, Rui Wang, Yan Guo, Wei Chen, Jie Feng, Jianfeng Wu

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A Scalable Ensemble Learning-Based Model for Optimal Placement of Circuit Breaker and Sectionalizer in Power Distribution Systems with the Aim of Reliability Improvement by Mehrdad Ebrahimi, Mohammad Rastegar

“…This paper proposes employing ensemble learning methods and explainable artificial intelligence tools to build an accurate data-driven model. …”
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Research on the Relationship between Business Cycle and Industrial Fluctuations in Northeast China Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise by Yinan Zhou, Guofeng Gu, Qiushuang Ren

“…The relationship between economic and industrial fluctuations in the three provinces of Northeast China was reexamined from the angle of fluctuation components with the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm. …”
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