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modelling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
codes algorithm » colony algorithm (Expand Search), cosine algorithm (Expand Search)
data codes » data models (Expand Search)
element » elements (Expand Search)
modelling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
codes algorithm » colony algorithm (Expand Search), cosine algorithm (Expand Search)
data codes » data models (Expand Search)
element » elements (Expand Search)
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Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…The fractional repetition (FR) code is a class of regenerating codes that consists of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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conferenceObject -
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Information reconciliation through agent controlled graph model. (c2018)
Published 2018“…Multiple models have been proposed and different techniques and data structures were used. …”
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masterThesis -
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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)
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masterThesis -
96
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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99
Label dependency modeling in Multi-Label Naïve Bayes through input space expansion
Published 2024“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”
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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. …”