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data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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121
Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023“…PubMed, Google Scholar, Science Direct, BioRXiv, and MedRxiv were explored to identify relevant articles. Study selection and data extraction were independently conducted by 2 reviewers. …”
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122
Nested ensemble selection: An effective hybrid feature selection method
Published 2023“…It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. …”
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Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
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124
EEG Signal Processing for Medical Diagnosis, Healthcare, and Monitoring: A Comprehensive Review
Published 2023“…This is because EEG visual analysis can be complex and time-consuming, as it mostly involves high dimensions and consists of large datasets. The development of novel sensors for EEG recording, digital signal processing algorithms, feature engineering, and detection algorithms increases the need for efficient diagnostic systems. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk
Published 2025“…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …”
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128
Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
Published 2023“…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …”
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129
Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective
Published 2024“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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133
A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”
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An Ontology-based Semantic Web for Arabic Question Answering: The Case of E-Government Services
Published 2018“…Further, 414 automatic questions are tested on the QA algorithm using two methods, semantics-based and keyword-based. …”
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135
Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review
Published 2021“…Of the 47 studies, we were able to classify the approaches taken by the studies into 3 different categories: 26 (55%) studies predicted cardiac arrest by analyzing specific parameters or variables of the patients, whereas 16 (34%) studies developed an AI-based warning system. The remaining 11% (5/47) of studies focused on distinguishing patients at high risk of cardiac arrest from patients who were not at risk. …”
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Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …”
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A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …”
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