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modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
making algorithm » cosine algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
data making » data mining (Expand Search)
modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
making algorithm » cosine algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
data making » data mining (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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103
The Use of Microwave Tomography in Bone Healing Monitoring
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doctoralThesis -
104
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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The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns
Published 2024“…AI technologies offer significant advantages, such as data-driven insights, improved efficiency, and enhanced predictive capabilities, which can support educational leaders in making more informed decisions. …”
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106
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 -
113
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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Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. …”
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Boosting the visibility of services in microservice architecture
Published 2023“…In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …”
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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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