Cloud and IoT based smart agent-driven simulation of human gait for detecting muscles disorder by Sina Saadati, Abdolah Sepahvand, Mohammadreza Razzazi

“…Additionally, a deep learning-based ensemble framework is proposed to assist in the analysis of the simulation results, offering both accuracy and interpretability. …”
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Analysis of Multidimensional Clinical and Physiological Data with Synolitical Graph Neural Networks by Mikhail Krivonosov, Tatiana Nazarenko, Vadim Ushakov, Daniil Vlasenko, Denis Zakharov, Shangbin Chen, Oleg Blyus, Alexey Zaikin

“…To apply Geometric Deep Learning we propose a synolitic or ensemble graph representation of the data, a universal method that transforms any multidimensional dataset into a network, utilising only class labels from training data. …”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…This study adopts a novel approach by utilizing hybrid models, which offer greater accuracy than individual or ensemble ML models. Specifically, support vector regression (SVR) was combined with three optimization algorithms: firefly algorithm (FFA), particle swarm optimization (PSO), and grey wolf optimization (GWO) to create hybrid models for estimating the SE of carbon fiber-reinforced mortars. …”
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La décroissance soutenable comme politique de sobriété by Yves-Marie Abraham

“…C’est en substance ce que revendiquent les partisans de la « décroissance soutenable », dont le programme se résume en trois points : produire moins, partager plus, décider ensemble. Reste à préciser l’horizon de mise en oeuvre de ces principes. …”
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Machine learning for medical image classification by Gazi Husain, Jonathan Mayer, Molly Bekbolatova, Prince Vathappallil, Mihir Matalia, Milan Toma

“…It navigates through various ML methods utilized in healthcare, including Supervised Learning, Unsupervised Learning, Self-Supervised Learning, Deep Neural Networks, Reinforcement Learning, and Ensemble Methods. The challenge lies not just in the selection of an ML algorithm but in identifying the most appropriate one for a specific task as well, given the vast array of options available. …”
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ICEEMDAN–VMD denoising method for enhanced magnetic memory detection signal of micro-defects by Shouhong Ji, Jie Yan, Yang Liu, Guojun He

“…When improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is employed independently for signal denoising, the noise and feature signals of the transition components are retained or removed. …”
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An Improved Demand Forecasting Model Using Deep Learning Approach and Proposed Decision Integration Strategy for Supply Chain by Zeynep Hilal Kilimci, A. Okay Akyuz, Mitat Uysal, Selim Akyokus, M. Ozan Uysal, Berna Atak Bulbul, Mehmet Ali Ekmis

“…The other novelty of this work is the adaptation of boosting ensemble strategy to demand forecasting system by implementing a novel decision integration model. …”
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XAI-Enhanced Machine Learning for Obesity Risk Classification: A Stacking Approach With LIME Explanations by Mohammad Azad, Md Faraz Kabir Khan, Sameh Abd El-Ghany

“…Our proposed model employs an ensemble approach, specifically a stacking algorithm, where the base estimators include the Light Gradient Boosting Machine (LGBM) classifier, the Logistic Regression (LR) classifier, and the Random Forest (RF) Classifier, and the Stochastic Gradient Descent (SGD) classifier is selected as the final estimator. …”
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Aggressive Aerosol Mitigation Policies Reduce Chances of Keeping Global Warming to Below 2C by R. Wood, M. A. Vogt, I. L. McCoy

“…Using the approximate partial radiative perturbation (APRP) method, future shortwave aerosol effective radiative forcing changes are isolated from other shortwave changes in an 18‐member ensemble of ScenarioMIP projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). …”
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A Diagnostic and Performance System for Soccer: Technical Design and Development by Alberto Gascón, Álvaro Marco, David Buldain, Javier Alfaro-Santafé, Jose Victor Alfaro-Santafé, Antonio Gómez-Bernal, Roberto Casas

“…Results indicate high accuracy rates for detecting ball-striking events and CoDs, with improvements in algorithm performance achieved through adaptive thresholds and ensemble neural network models. Compared to existing systems, this approach significantly reduces costs and enhances practicality by minimizing the number of sensors required while ensuring real-time evaluation capabilities. …”
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PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations by Fahmida Khanom, Mohammad Shorif Uddin, Rafid Mostafiz

“…This study introduces an ensemble boosting machine, termed PD_EBM, for the detection of PD. …”
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A hybrid Framework for plant leaf disease detection and classification using convolutional neural networks and vision transformer by Sherihan Aboelenin, Foriaa Ahmed Elbasheer, Mohamed Meselhy Eltoukhy, Walaa M. El-Hady, Khalid M. Hosny

“…This proposed model leverages the strength of Convolutional Neural Networks (CNNs) and Vision Transformers (ViT), where an ensemble model, which consists of the well-known CNN architectures VGG16, Inception-V3, and DenseNet20, is used to extract robust global features. …”
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Identification of multiple power quality disturbances in hybrid microgrid using deep stacked auto-encoder based bi-directional LSTM classifier by Ravi Kumar Jalli, Lipsa Priyadarshini, P.K. Dash, Ranjeeta Bisoi

“…Thus to design an effective PQD recognition system, this paper proposes a novel time-frequency analysis method based on adaptively fast complementary ensemble local mean decomposition (AFCELMD) technique that decomposes the multicomponent PQD signal into a series of demodulated product functions (PFs). …”
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Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma by Mengmeng Hua, Tao Li

“…LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somatic mutation data from The Cancer Genome Atlas LUAD cohort were analyzed to identify lactylation cancer subtypes (CSs) using 10 multiomics ensemble clustering techniques. The findings were then validated using the GSE31210 and GSE13213 LUAD cohorts. …”
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Annotation-free deep learning for predicting gene mutations from whole slide images of acute myeloid leukemia by Bo-Han Wei, Xavier Cheng-Hong Tsai, Kuo-Jui Sun, Min-Yen Lo, Sheng-Yu Hung, Wen-Chien Chou, Hwei-Fang Tien, Hsin-An Hou, Chien-Yu Chen

“…We, therefore, propose a deep learning model based on multiple instance learning (MIL) with ensemble techniques to predict gene mutations from AML WSIs. …”
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Developing a brain inspired multilobar neural networks architecture for rapidly and accurately estimating concrete compressive strength by Bashar Alibrahim, Ahed Habib, Maan Habib

“…Moreover, it is compared against two traditional cases, ANN and ensemble learning neural networks (ELNN). The study results indicated that the MLANN architecture significantly improves the estimation performance, reducing the root mean square error by up to 32.9% and mean absolute error by up to 25.9% while also enhancing the A20 index by up to 17.9%, ensuring a more robust and generalizable model. …”
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CIMA: A Novel Classification-Integrated Moving Average Model for Smart Lighting Intelligent Control Based on Human Presence by Aji Gautama Putrada, Maman Abdurohman, Doan Perdana, Hilal Hudan Nuha

“…Several classification models are proposed and compared, namely, k-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), näive Bayes (NB), and ensemble voting (EV). We build an Internet of things (IoT) system to collect movement data. …”
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Interval combined prediction of mine tunnel's air volume considering multiple influencing factors. by Zhen Wang, Erkan Topal, Liangshan Shao, Chen Yang

“…These interval numbers are then preprocessed using an Interval-type Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(In-CEEMDAN) to extract the essential features of the data. …”
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Moments of axial-vector GPD from lattice QCD: quark helicity, orbital angular momentum, and spin-orbit correlation by Shohini Bhattacharya, Krzysztof Cichy, Martha Constantinou, Xiang Gao, Andreas Metz, Joshua Miller, Swagato Mukherjee, Peter Petreczky, Fernanda Steffens, Yong Zhao

“…The calculations are based on an N f = 2 + 1 + 1 twisted mass fermions ensemble with clover improvement, a lattice spacing of a = 0.093 fm, and a pion mass of m π = 260 MeV. …”
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Stimulated Reservoir Volume Characterization and Optimum Lateral Well Spacing Study of Two-Well Pad: Midland Basin Case Study by Jaeyoung Park, Candra Janova

“…The population-based history matching algorithm provides the ensemble of the history-matched model, and the top 50 history-matched models were selected to predict the range of Estimate Ultimate Recovery (EUR), showing that P50 of oil EUR is within the acceptable range of the deterministic EUR estimates. …”
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