Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 171 for “"supervised machine learning"”.
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GOES-R Supervised Machine Learning
… we explore different artificial intelligence, machine learning algorithms to detect image anomalies which has broader flagging applications than just correcting for temperatures.</p>
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Improving supervised machine learning for materials science
Despite the widespread applications of machine learning models in materials science, in many cases the performance of machine learning models is not sufficiently accurate enough to meet the needs of materials design. In this thesis, we propose and apply a series of strategies to exam and improve …
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Weakly Supervised Machine Learning for Cyberbullying Detection
… detection in social media by developing machine-learning framework that only requires weak supervision. We propose a general framework that trains an ensemble of two learners in which each learner looks at the problem from a different perspective. One learner identifies bullying incidents …
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Predicting anomalous weather events using supervised machine learning
… There is a growing interest in the use of machine learning techniques as an alternative to traditional weather forecasting methods. In this study, the use of machine learning techniques to predict daily maximum temperatures and detect temperature anomalies is investigated. Machine learning …
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Applying Supervised Machine Learning Techniques to Municipal Bond Trading
… we will examine how artificial intelligence or machine learning can be used to make better municipal bond trading decisions. The paper will examine a variety of classification models trained in a supervised environment. The paper will discuss: i. How to prepare data for machine learning analysis …
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Supervised Machine Learning Techniques for Short-Term Load Forecasting
… for energy management based on the demand. Machine Learning Algorithms has been in the forefront for prediction algorithms. This Thesis is mainly aimed to provide utility companies with a better insight about the wide range of Techniques available to forecast the load demands based on …
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A Systems Theory Approach to Cybersecuring a Supervised Machine Learning System
Machine learning is a rapidly growing field with many applications in areas such as healthcare, finance, and transportation. As machine learning becomes more prevalent, it is important to ensure that these systems are secure and can resist attacks from malicious actors. This is particularly …
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Exploring the Use of Supervised Machine Learning Algorithms to Classify Simulated Balance Deficits
… was to determine the achievable accuracies of supervised machine learning algorithms for classifying simulated balance deficits and the number of participants needed to maximize those accuracies. The long-term goal is to create a classification system that can accurately detect the presence, …
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Characterization of the Operational Trna Code for Amino Acids Through Supervised Machine Learning
… code is universal or taxon-specific. Using supervised machine-learning classifiers trained on tRNA sequences, we found that the anticodon is not the sole determinant of tRNA identity. Even when the anticodon region was removed, classification accuracy remained high, indicating that other …
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BACTERIA ANALYSIS BY USING A SUPERVISED MACHINE LEARNING ALGORITHM BASED ON DROPLET MICROFLUIDICS
… By using droplet microfluidics and a machine learning algorithm, the objective of this study was to propose a technology that analyzes images of bacterial cells by image processing and Support Vector Machines algorithm to classify droplets containing the bacteria. The accuracy of the …
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Geosynchronous Satellite Maneuver Classification and Orbital Pattern Anomaly Detection via Supervised Machine Learning
Due to the nature of the geosynchronous (GEO) orbital regime, where space objects orbit the Earth once per sidereal day, GEO satellites can appear fixed to a position in the sky when observed from the Earth’s surface. This unique orbital characteristic makes GEO satellites ideal for …
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Geosynchronous Satellite Maneuver Classification and Orbital Pattern Anomaly Detection via Supervised Machine Learning
Due to the nature of the geosynchronous (GEO) orbital regime, where space objects orbit the Earth once per sidereal day, GEO satellites can appear fixed to a position in the sky when observed from the Earth’s surface. This unique orbital characteristic makes GEO satellites ideal for …
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Optimization and Supervised Machine Learning Methods for Inverse Design of Cellular Mechanical Metamaterials
… the Monte Carlo method, this study utilizes a machine learning technique to bypass the expensive simulations to compute properties. In addition to reducing the computational expense of the simulations, the deep learning method has been proven to be practical to accomplish non-intuitive design …
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Supervised Machine Learning Under Test-Time Resource Constraints: A Trade-off Between Accuracy and Cost
<p>The past decade has witnessed how the field of machine learning has established itself as a necessary component in several multi-billion-dollar industries. The real-world industrial setting introduces an interesting new problem to machine learning research: computational resources must be …
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A supervised machine learning-based framework to detect low-level fault injections in software systems
… utilize system-specific software features and unsupervised learning due to lack of labelled data. Unsupervised pattern recognition is vulnerable to false data injection, and Machine Learning algorithms such as Artificial and Recurrent Neural Networks are not feasible for resource-constrained …
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Implementation and comparative analysis of supervised machine learning methods for domain modeling and grade estimation techniques
… introduce errors early in the modeling process. Supervised Machine learning (ML) offers a promising alternative, capable of handling complex data sets for domain analysis and grade estimation. This research introduces novel geospatial estimation methods, validated through a case study on …
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Development of a connected platform for industrial equipment monitoring to enable predictive maintenance using supervised machine learning methods
… products. SHAPE has historically outfitted its machines with a suite of sensors, however these systems in the field do not store the data, thereby losing the time series relationships and historical log of machine health. One opportunity is to create a connected platform that leverages this data …
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A supervised machine-learning method for detecting steady-state visually evoked potentials for use in brain computer interfaces: A comparative assessment
It is hypothesised that supervised machine learning on the estimated parameters output by a model for visually evoked potentials (VEPs), created by Kremlácek et al. (2002), could be used to classify steady-state visually evoked potentials (SSVEP) by frequency of stimulation. Classification of …
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