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prediction models » predictive models (Expand Search)
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Combining and adapting software quality predictive models by genetic algorithms
Published 2017“…The goal of quality models is to predict a quality factor starting from a set of direct measures. …”
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Model predictive control of shell benchmark process
Published 2003“…In this paper model predictive controller is proposed for the control of a two-input-two-output high purity shell distillation column. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data. …”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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Transfer learning for genotype–phenotype prediction using deep learning models
Published 2022“…If the large population data is extensive compared to small population data, expect transfer learning results to improve significantly. We show that Transfer learning is capable to create powerful models for genotype-phenotype predictions in large, well-studied populations and fine-tune these models to populations were data is sparse.…”
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Scatter search for protein structure prediction. (c2008)
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Inverse Model Predictive Control for Power Electronic Converters
Published 2024“…<p dir="ltr">In this paper, a new control technique called inverse model predictive control (IMPC) is proposed for power electronic converters. …”
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A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity
Published 2024“…Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable <u>bioluminescence </u>activity of NLuc in living cells and in vitro. …”
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Development of Seed Variables Prediction Models for Use in Dynamic Backcalculation of FWD Data
Published 2022“…This research project aims-to-develop models through classification analysis to predict the seed variables. …”
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PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks
Published 2022“…<h3>Background</h3><p dir="ltr">Early identification of pregnant women at risk for preterm birth (PTB), a major cause of infant mortality and morbidity, has a significant potential to improve prenatal care. However, we lack effective predictive models which can accurately forecast PTB and complement these predictions with appropriate interpretations for clinicians. …”
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The significance of ferrous ion oxidation during corrosion of carbon steel in aerated near-neutral aqueous solutions
Published 2023“…<p dir="ltr">Numerical models were developed to investigate the significance of ferrous ion oxidation in carbon steel corrosion in near-neutral aerated aqueous solutions. …”
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Prediction of the Backwater Level Due to Bridge Constriction in Waterways
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Forecasting model to predict project success based on the contractors’ characteristics
Published 2018Get full text
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Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…In both predictions, we demonstrate a significant improvement compared to previous work on the same dataset and we highlight the importance of traffic and weather information for charging behavior predictions.…”
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Detection of statistically significant network changes in complex biological networks
Published 2017“…</p><h3>Methods</h3><p dir="ltr">In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. The proposed procedure exploits a more effective model selection criteria to generate <i>p</i>-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. …”
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AI-based remaining useful life prediction and modelling of seawater desalination membranes
Published 2024Get full text
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Developing a Stochastic Model to Predict Cost Overrun due to the Causes of Projects Delay in Oil Fields Construction Industry
Published 2020“…However, most of the causes of cost overrun were found to follow the Log logistic distribution – a family of distribution associated with projects where the risk increases at the initial phase of the project and decreases later on. …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
Published 2024Get full text
doctoralThesis