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models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
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Deploying model obfuscation: towards the privacy of decision-making models on shared platforms
Published 2024“…This research is expected to develop into deployable model obfuscation technique which practitioners from the industrial domain can adopt.…”
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63
Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…The resulting model achieves an 89% predictive accuracy using historical data. …”
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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…In this paper, the most important literature and previous studies related to the subject of the study were presented, where nearly 30 researches were referred to develop a theoretical framework related to SSA and other improved algorithms and to compare SSA with other systems. …”
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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. …”
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Scatter search for protein structure prediction. (c2008)
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masterThesis -
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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Developing a UAE-Based Disputes Prediction Model using Machine Learning
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doctoralThesis -
69
Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”
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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective
Published 2024“…Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control
Published 2021“…The proposed model predictive control framework is flexible and can be applied to other greenhouse systems by tuning the model on the new data set.…”
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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masterThesis -
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
Published 2022“…Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. …”
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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.…”