A Novel Hybrid Model for Short-Term Wind Speed Forecasting Based on Twice Decomposition, PSR, and IMVO-ELM by Xin Xia, Xiaolu Wang

“…In consideration of the nonstationarity of the wind speed signal, a twice decomposition based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), fuzzy entropy, and variational mode decomposition (VMD) is proposed to reduce the nonstationarity of the original signal firstly. …”
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De la tourismification d’un village au déplacement de sa population : expressions d’un rapport hiérarchique entre l’État chinois et la nationalité minoritaire wa by Sarah Coulouma

“…La mise en tourisme du village wa de Wengding, surnommé la « dernière tribu primitive » de Chine par les acteurs public et privé de sa promotion touristique, repose sur un ensemble d’installations et d’aménagements de l’espace villageois et des activités touristiques qui tendent à objectiver la primitivité de la « culture de la nationalité wa », voire des Wa eux-mêmes. …”
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A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees by Joaquín Abellán, Javier G. Castellano, Carlos J. Mantas

“…It will be shown that the bagging ensemble using pruned credal trees outperforms the successful bagging C4.5 and RF when data sets with medium-to-high noise level are classified.…”
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A Mini-Review of Machine Learning in Big Data Analytics: Applications, Challenges, and Prospects by Isaac Kofi Nti, Juanita Ahia Quarcoo, Justice Aning, Godfred Kusi Fosu

“…The study outcome shows that deep neural networks (15%), support vector machines (15%), artificial neural networks (14%), decision trees (12%), and ensemble learning techniques (11%) are widely applied in BDA. …”
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Multifaceted changes in water availability with a warmer climate by Binglan Gu, Sha Zhou, Bofu Yu, Kirsten L. Findell, Benjamin R. Lintner

“…We develop a multi-model ensemble approach to classify global terrestrial hydroclimate into four distinct regimes based on the mean and seasonality of P-E. …”
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A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats by Dheyaaldin Alsalman

“…In this study, we introduce FusionNet, an innovative ensemble model that combines the strengths of multiple machine learning algorithms, namely Random Forest, K-Nearest Neighbors, Support Vector Machine, and Multi-Layer Perceptron, for enhanced anomaly detection. …”
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Convolutional Recurrent Neural Network for Fault Diagnosis of High-Speed Train Bogie by Kaiwei Liang, Na Qin, Deqing Huang, Yuanzhe Fu

“…By comparing the performance of the presented CRNN with CNN, RNN, and ensemble learning, experimental results show that CRNN achieves not only the best performance with accuracy of 97.8% but also the least time spent in training model.…”
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Thermodynamics of Charged Rotating Dilaton Black Branes Coupled to Logarithmic Nonlinear Electrodynamics by A. Sheykhi, M. H. Dehghani, M. Kord Zangeneh

“…We study thermal stability of the solutions in both canonical and grand-canonical ensemble and disclose the effects of the rotation parameter, nonlinearity of electrodynamics, and dilaton field on the thermal stability conditions. …”
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A Full Stage Data Augmentation Method in Deep Convolutional Neural Network for Natural Image Classification by Qinghe Zheng, Mingqiang Yang, Xinyu Tian, Nan Jiang, Deqiang Wang

“…In this paper, we propose a full stage data augmentation framework to improve the accuracy of deep convolutional neural networks, which can also play the role of implicit model ensemble without introducing additional model training costs. …”
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Design and Evaluation of a Hybrid Technique for Detecting Sunflower Leaf Disease Using Deep Learning Approach by Arun Malik, Gayatri Vaidya, Vishal Jagota, Sathyapriya Eswaran, Akash Sirohi, Isha Batra, Manik Rakhra, Evans Asenso

“…VGG-16 and MobileNet are two transfer learning models that are used for classification purposes, and the stacking ensemble learning approach is used to merge them or create a hybrid model from the two models. …”
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MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank by Fan Cheng, Wei Guo, Xingyi Zhang

“…Then on the selected instance subsets, a multiobjective feature selection algorithm with an adaptive mutation is developed, where good feature subsets are obtained by selecting the features with high ranking accuracy and low redundancy. Finally, an ensemble strategy is also designed in MOFSRank, which utilizes these obtained feature subsets to produce a set of better features. …”
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Imbalanced Data Problem in Machine Learning: A Review by Manahel Altalhan, Abdulmohsen Algarni, Monia Turki-Hadj Alouane

“…It discusses data-level methods such as oversampling and undersampling, algorithm-level solutions including ensemble learning and specific algorithm adjustments, cost-sensitive algorithms, and hybrid strategies that combine multiple approaches. …”
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Validation of the New Algorithm for Rain Rate Retrieval from AMSR2 Data Using TMI Rain Rate Product by Elizaveta Zabolotskikh, Bertrand Chapron

“…Simultaneous meteorological and hydrological observations, supplemented with modeled values of cloud liquid water content and rain rate values, are used for the calculation of an ensemble of AMSR2 TBs and RRs. Ice clouds are not taken into account. …”
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Automatic Emergence Detection in Complex Systems by Eugene Santos, Yan Zhao

“…We evaluate our detection performance against a baseline approach (Bayesian Network ensemble) on synthetic testbeds from UCI datasets. …”
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Genetic Vectors as a Tool in Association Studies: Definitions and Application for Study of Rheumatoid Arthritis by Igor Sandalov, Leonid Padyukov

“…To identify putative relations between different genetic factors in the human genome in the development of common complex disease, we mapped the genetic data to an ensemble of spin chains and analysed the data as a quantum system. …”
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An Improved CEEMDAN Time-Domain Energy Entropy Method for the Failure Mode Identification of the Rolling Bearing by Fengfeng Bie, Yi Miao, Fengxia Lyu, Jian Peng, Yue Guo

“…Aiming at that the extraction of rolling bearing fault features and traditional support vector machine parameters affects the overall accuracy of pattern classification, the improved CEEMDAN (complete ensemble empirical mode decomposition with adaptive noise) time-domain energy entropy-based model for fault pattern recognition is proposed. …”
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Decomposition-Based Multistep Sea Wind Speed Forecasting Using Stacked Gated Recurrent Unit Improved by Residual Connections by Jupeng Xie, Huajun Zhang, Linfan Liu, Mengchuan Li, Yixin Su

“…The predictors have 24 inputs and 3 outputs, and the forecast is an ensemble of five predictors’ outputs. The proposed model can predict wind speed in the next 3 hours according to the past 24 hours’ wind speed data. …”
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Payerne VD, Abbatiale. Kapitelsaal und Marienkapelle – Stand der Forschung by Guido Faccani

“…Avec les autres éléments architecturaux, le plan d’ensemble du monastère peut être reconstitué ; il présente des ressemblances avec celui de Villars-les-Moines.…”
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Performance of International Global Models and Official Tropical Cyclone Forecasts Over the Bien Dong Sea for the Period 2012–2019 by Hoa Vo Van, Hung Mai Khanh, Tien Du Duc, Lars Robert Hole, Quan Dang Dinh, Duc Tran Anh, Hang Pham Thi, Nam Hoang Gia

“…Regarding the ECMWF’s ensemble track forecast, the strike probability forecast is quite overforecast/overconfident, especially for a lead time of 72 h and at high probabilities.…”
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Dynamical suppression of many-body non-Hermitian skin effect in anyonic systems by Yi Qin, Ching Hua Lee, Linhu Li

“…The spreading of quantum information in this system shows even more exotic phenomena, where NHSE affects only the information dynamics for a thermal ensemble, but not that for a single initial state. …”
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