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modeling algorithm » scheduling algorithm (Expand Search)
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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”
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Scatter search for protein structure prediction. (c2008)
Published 2008Get full text
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Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…The methodology involves data preparation with <u>imputation</u> and normalization, followed by training 9 supervised ML models. …”
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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“…Our experimental design included Data Collection, Feature Engineering, ML model selection/development, and reporting evaluation of metrics.…”
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…</p><h3>Methods</h3><p dir="ltr">Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. …”
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Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation
Published 2022“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”
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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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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE
Published 2018“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
Published 2022“…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”
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