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Showing result 1 - 5 of 56 essays matching the above criteria.
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1. Using Machine Learning to Optimize Near-Earth Object Sighting Data at the Golden Ears Observatory
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This research project focuses on improving Near-Earth Object (NEO) detection using advanced machine learning techniques, particularly Vision Transformers (ViTs). The study addresses challenges such as noise, limited data, and class imbalance. READ MORE
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2. USING ARTIFICIAL NETWORKS IN COMPLEX PROBLEMS ANALYSING PARAMETERS INFLUENCE
University essay from Mälardalens universitet/Akademin för innovation, design och teknikAbstract : Mathematical statistical models are insufficient for describing complex phenomena. In contrast, Artificial Neural Networks (ANNs), have been used across various complex problem domains for solving problems. ANNs can learn complex patterns and capture non-linear relationships between parameters. READ MORE
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3. Synthesis of Neural Networks using SAT Solvers
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Artificial neural networks (ANN) have found extensive use in solving real-world problems in recent years, where their exceptional information processing is the main advantage. Facing increasingly complex problems, there is a need to improve their information processing. READ MORE
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4. Physics-Enhanced Machine Learning for Energy Systems
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Building operations account for a large amount of energy usage and the HVAC (Heating, Ventilation and Air Conditioning) systems are the largest consumer of energy in this sector. To reduce this demand, more energy-efficient control algorithms are implemented and a popular choice for a controller is the model predictive control. READ MORE
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5. Solving Differential Equations using Data-Driven Adaptive Numerical Method
University essay from KTH/Skolan för teknikvetenskap (SCI)Abstract : Accuracy and efficiency have always been of great concern when solving differential equations. One approach to improve accuracy is by introducing a neural network, whose role is to learn the local truncation error (LTE) of a numerical method. READ MORE