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181
Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”
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182
Bee Colony Algorithm for Proctors Assignment.
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…<p dir="ltr">Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …”
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Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence
Published 2020“…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …”
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186
Data Redundancy Management in Connected Environments
Published 2020“…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
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187
Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”
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188
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Published 2023“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”
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189
Android Malware Detection Using Machine Learning
Published 2024“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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190
Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis
Published 2021“…In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …”
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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023“…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”
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Graph Contraction for Mapping Data on Parallel Computers
Published 1994“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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197
Mapping realistic data sets on parallel computers
Published 1993“…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
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198
Parallel genetic algorithm for disease-gene association
Published 2011“…In this work, we combine few successful strategies from the literature and present a parallel genetic algorithm for the Tag SNP Selection problem. Our results compared favorably with those of a recognized tag SNP selection algorithm using three different data sets from the HapMap project.…”
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Particle swarm optimization algorithm: review and applications
Published 2024“…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
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