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pollination algorithm » optimization algorithm (Expand Search)
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pollination algorithm » optimization algorithm (Expand Search)
data pollination » data duplication (Expand Search)
data selection » data injection (Expand Search)
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81
An Alternating Projection Framework for Elementwise Masked Nonlinear Matrix Decomposition
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doctoralThesis -
82
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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83
Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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masterThesis -
84
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …”
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86
Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes
Published 2025“…In the first stage, we performed binary classification, grouping SAH severity into “Good Outcome” (class 0), which includes MRS levels 0, 1, 2, and 3, and “Poor Outcome” (class 1), encompassing levels 4, 5, and 6. Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”
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87
The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”
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88
A novel hybrid methodology for fault diagnosis of wind energy conversion systems
Published 2023“…In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”
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89
The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review
Published 2022“…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …”
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91
An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization
Published 2022“…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …”
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92
Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet
Published 2025“…A hybrid feature selection technique integrates the Boruta algorithm and SHAP (SHapley Additive exPlanations) values to ensure robust feature selection. …”
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network
Published 2020“…In the first phase, data preprocessing and feature selection technique is applied to the collected dataset. …”
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95
Video features with impact on user quality of experience
Published 2021“…The feature evaluation is performed first using forward elimination feature selection algorithm, and second using decision tree classification to extract and sort the features that highly affect the subjective QoE. …”
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conferenceObject -
96
A geographic information system method to generate long term regional solar radiation resource maps: enhancing decision-making
Published 2024“…The availability of solar radiation throughout the country has been mapped here using ground-based measurements and satellite data. The regression-kriging algorithm and its variants are used to calibrate satellite data, through interpolation of ground solar radiation data. …”
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97
Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review
Published 2021“…Backward reference list checks of the included studies were also conducted. Study selection and data extraction were independently conducted by 2 reviewers. …”
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98
An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation
Published 2019“…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …”
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article -
99
Resource allocation scheme for eMBB and uRLLC coexistence in 6G networks
Published 2023“…An optimal resource allocation scheme is proposed with two scenarios including a guaranteed fairness level and minimum data rate among eMBB users. In addition, a knapsack-inspired punctured resource allocation algorithm is proposed where the users’ channel qualities of both services are considered at each time slot leading to the most suitable Resource Block (RB) selection for puncturing in a way that minimizes the negative impact on eMBB performance. …”
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100
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. …”