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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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83
Minimum UAV fog servers with maximum IoT devices association using genetic algorithms
Published 2021“…IoT created many challenges as the services response time requirements have grown more strict and urged the need for faster means of communications and computation processing. …”
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conferenceObject -
84
A Multi-Channel Convolutional Neural Network approach to automate the citation screening process
Published 2021“…This study aims to automate the citation screening process using Deep Learning algorithms. With this, it is aimed to reduce the time and costs of the citation screening process and increase the precision and recall of the relevant primary studies. …”
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
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87
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 -
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Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
Published 2020“…The performance of the EMA-based SHM is presented showing experimental results considering a reduced number of switching angles applied to a specific three-level converter, but the method can be extrapolated to any other three-level converter topology.…”
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89
Applying urban parametric design optimisation processes to a hot climate: Case study of the UAE
Published 2014“…Parametric and algorithmic design is considered a current trend in architectural design processes. …”
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System
Published 2024“…Furthermore, a higher value of the fl is preferred to guide the optimization process in the direction of global search, whilst a lower fl value directs the algorithm in the direction of local search. …”
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92
Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”
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93
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment
Published 2022“…Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period for scheduling tasks in a heterogeneous environment. …”
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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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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…The provided data facilitate precise replication of the output, saving significant simulation time. Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…”
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Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks
Published 2025“…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…”
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A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model
Published 2021“…Gaussian Process Regression (GPR) with Fit a Gaussian process regression model (Fitrgp) feature selection algorithm outperformed all other combinations and exhibits a root mean squared error (RMSE), mean absolute error (MAE), and two-standard deviation (2SD) of 2.63, 1.97, and 5.25 breaths per minute, respectively. …”
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The operating cost of a residential building is reduced by using a day-ahead scheduling process for controlling multiple energy sources to create a reliable look-up table that estimates the best schedule for the distributed energy sources at each time frame. …”
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100
Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The operating cost of a residential building is reduced by using a day-ahead scheduling process for controlling multiple energy sources to create a reliable look-up table that estimates the best schedule for the distributed energy sources at each time frame. …”