Learners Reliability Estimated Through Neural Networks Applied to Build a Novel Hybrid Ensemble Method
Sign Up to like & getrecommendations! Published in 2017 at "Neural Processing Letters"
DOI: 10.1007/s11063-017-9586-6
Abstract: In this paper a novel hybrid ensemble method aiming at the improvement of models accuracy in regression tasks is presented. The basic idea of the approach is the creation of an ensemble learner composed by… read more here.
Keywords: reliability estimated; ensemble method; hybrid ensemble; learners reliability ... See more keywords
Hybrid ensemble model for differential diagnosis between COVID-19 and common viral pneumonia by chest X-ray radiograph
Sign Up to like & getrecommendations! Published in 2021 at "Computers in Biology and Medicine"
DOI: 10.1016/j.compbiomed.2021.104252
Abstract: Background Chest X-ray radiography (CXR) has been widely considered as an accessible, feasible, and convenient method to evaluate suspected patients’ lung involvement during the COVID-19 pandemic. However, with the escalating number of suspected cases, traditional… read more here.
Keywords: ensemble model; hybrid ensemble; covid; model ... See more keywords
A hybrid ensemble learning framework for basketball outcomes prediction
Sign Up to like & getrecommendations! Published in 2019 at "Physica A: Statistical Mechanics and its Applications"
DOI: 10.1016/j.physa.2019.121461
Abstract: Abstract Basketball outcomes prediction is a vital technique for prospective player arrangement, injury avoidance, telecast right pricing, etc., which requires a understanding of the skill, luck, and other exterior factors of both teams. This paper… read more here.
Keywords: hybrid ensemble; ensemble learning; outcomes prediction; basketball ... See more keywords
A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2018.1458988
Abstract: ABSTRACT Geo-tagged travel photos on social networks often contain location data such as points of interest (POIs), and also users’ travel preferences. In this paper, we propose a hybrid ensemble learning method, BAyes-Knn, that predicts… read more here.
Keywords: location; learning method; social networks; geo tagged ... See more keywords
Novel Deep Hybrid and Ensemble Algorithms for Improving GPS Navigation Positioning Accuracy
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DOI: 10.1109/access.2023.3272057
Abstract: GPS (Global Positioning System) has been a widespread system used for various purposes in today’s world and it is essential to suggest innovative effective solutions to improve its use and functions. The present study proposes… read more here.
Keywords: accuracy; hybrid ensemble; positioning accuracy; ensemble algorithms ... See more keywords
Leveraging Lightweight Hybrid Ensemble Distillation (HED) for Suspect Identification With Face Recognition
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2024.3523101
Abstract: Face recognition biometric systems focus on identifying individuals by extracting their facial characteristics. However, these systems often fail or are misclassified because of external factors, obstructions, and varying environmental conditions. Traditional models cannot effectively handle… read more here.
Keywords: hybrid ensemble; ensemble distillation; face recognition; distillation ... See more keywords
Hybrid Ensemble Learning Model Combining BERT and CNN for Predicting Urban Rail Transit Accident Consequences
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2025.3580380
Abstract: Urban Rail Transit (URT) accidents not only seriously affect the safety and reliability of its operations, but also reduce service level to passengers. Based on historical URT accident data, this study develops a hybrid ensemble… read more here.
Keywords: accident consequences; hybrid ensemble; accident; ensemble learning ... See more keywords
Hybrid Ensemble Deep Learning for Deterministic and Probabilistic Low-Voltage Load Forecasting
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Power Systems"
DOI: 10.1109/tpwrs.2019.2946701
Abstract: Accurate and reliable low-voltage load forecasting is critical to optimal operation and control of distribution network and smart grid. However, compared to traditional regional load forecasting at high-voltage level, it faces tough challenges due to… read more here.
Keywords: hybrid ensemble; low voltage; voltage; load forecasting ... See more keywords
IoT-Based Hybrid Ensemble Machine Learning Model for Efficient Diabetes Mellitus Prediction
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/2389636
Abstract: Nowadays, there is a growing need for Internet of Things (IoT)-based mobile healthcare applications that help to predict diseases. In recent years, several people have been diagnosed with diabetes, and according to World Health Organization… read more here.
Keywords: machine learning; hybrid ensemble; iot based; model ... See more keywords
DPATransLLM: Detection of Pronominal Anaphora in Turkish Sentences Using Transformer-Based, Large Language Models and Hybrid Ensemble Approach
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DOI: 10.3390/app152312480
Abstract: In the current information age, with the exponential growth of data volume and language-based applications, the accurate resolution of intra-contextual relationships in texts has become indispensable for both academic research and industrial Natural Language Processing… read more here.
Keywords: pronominal anaphora; hybrid ensemble; detection pronominal; language ... See more keywords
HeartEnsembleNet: An Innovative Hybrid Ensemble Learning Approach for Cardiovascular Risk Prediction
Sign Up to like & getrecommendations! Published in 2025 at "Healthcare"
DOI: 10.3390/healthcare13050507
Abstract: Background: Cardiovascular disease (CVD) is a prominent determinant of mortality, accounting for 17 million lives lost across the globe each year. This underscores its severity as a critical health issue. Extensive research has been undertaken… read more here.
Keywords: ensemble learning; risk prediction; hybrid ensemble; heartensemblenet ... See more keywords