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.
Results
Showing 1 to 20 of 188 for “"machine learning algorithm"”.
-
Contributions to statistical machine learning algorithm
… are written as contributions to statistical machine learning algorithm literature.
-
Predicting the Price of Cryptocurrency Using Machine Learning Algorithm
… other than ethereum as well. We propose to use Machine Learning for this project, which will be trained from the available cryptocurrency price data, to gain intelligence, and then use this knowledge to make accurate predictions. Trading cryptocurrency prices is one of the most popular exchanges …
-
Physics Guided Machine Learning algorithm for MAX-DOAS retrieval
… it almost impossible to design an inversion algorithm providing a definite solution. A possible way to find a low-error inversion algorithm is incorporating the machine learning (ML) technique into the MAX-DOAS retrieval. This dissertation serves as the author's exploration of designing such …
-
A New Machine Learning Algorithm for Detection of Stray Clays
This paper discusses various machine learning algorithms utilized with Ground Penetrating Radar (GPR) for differentiating between clay seam number 414 and stray clays in potash mines to evaluate mine-room safety. Although different strategies have been used to find and recognize anomalies from GPR …
-
MACHINE LEARNING ALGORITHM PERFORMANCE OPTIMIZATION: SOLVING ISSUES OF BIG DATA ANALYSIS
… of high complexity of time and space, generating machine learning models for big data is difficult. This research is introducing a novel approach to optimize the performance of learning algorithms with a particular focus on big data manipulation. To implement this method a machine learning …
-
Behaviour based anomaly detection system for smartphones using machine learning algorithm
… of our experiment. Following this analysis, a Machine Learning algorithm was applied on the dataset to create a baseline usage profile for each participant. These profiles were compared to monitor deviations from baseline in a series of tests that we conducted, to determine the profiling …
-
Analyses and Applications of Seismic Surface Waves Using Machine Learning Algorithm
… their noise removal. I propose an unsupervised machine-learning algorithm using K-means clustering to automatically identify surface waves in the raw seismic data according to their common features, including low frequency, low velocity, and high amplitude when compared to body waves. The local …
-
Position Falsification Detection in VANET with Consecutive BSM Approach using Machine Learning Algorithm
… approach to detect malicious behavior, using machine learning (ML) algorithms.The proposed Machine Learning based misbehavior detection system utilizes labelled dataset called Vehicular Reference Misbehavior Dataset (VeReMi). VeReMi dataset offers five different types of position falsification …
-
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 …
-
A Proof of Concept for a Machine Learning Algorithm to Screen for Adolescent Idiopathic Scoliosis Using Images Captured with Modern Smartphone Technology
… a depth sensor to create a simple and effective machine learning (ML) algorithm that can detect the absence or presence of scoliosis. Secondarily, this thesis project aims to 1) provide a proof of concept for a regression-based ML algorithm that can predict the main curvature of the scoliotic …
-
Development of a Machine Learning Algorithm for the Estimation of Soil Organic Matter from the Integration of UAV and In-Ground Soil Sensor
… employing in-ground sensors inside the ML (Machine Learning) approach should produce a good correlation with the laboratory LOI (Loss on Ignition) tested samples. Two methods were used to gather the data: aerial images collected by UAVs displayed the vegetative index NDVI (Normalized …
-
Development of a Machine Learning Algorithm for the Estimation of Soil Organic Matter from the Integration of UAV and In-Ground Soil Sensor
… employing in-ground sensors inside the ML (Machine Learning) approach should produce a good correlation with the laboratory LOI (Loss on Ignition) tested samples. Two methods were used to gather the data: aerial images collected by UAVs displayed the vegetative index NDVI (Normalized …
-
DYNAMIC ANALYSIS OF PROGRAM EXECUTION TO DISCOVER USAGE CLASSES
… conditions. This research explores the use of machine learning techniques to predict an application’s usage class based on the analysis of its assembly-level instruction trace, working under the premise that processes which are similar in usage class will share similar low-level behavior and …
-
New interpretable machine learning techniques and an application to stroke prediction in atrial fibrillation patients
… are attracting more and more interest in the machine learning community. In this thesis, we developed an interpretable machine learning algorithm called SBRL and we built an interpretable and statistically more accurate model for predicting strokes for patients in atrial fabrication (AF) who …
-
Physics-assisted machine learning for X-ray imaging
… satisfactory reconstructions. Recently, deep learning has been adopted for 2D and 3D reconstruction. Unlike iterative algorithms which require a distribution that is known a priori, deep reconstruction networks can learn a prior distribution through sampling the statistical properties of the …
-
A Smart Energy-Efficient Hybrid Gait Monitoring System
… integrated into the shoe insoles and employs a machine learning algorithm to perform human activity recognition. Two scenarios were evaluated. First, where the triboelectric nanogenerators are used as the sensing unit, and the output voltage of the harvested energy serves as the gait signal for …
-
Generating Exploration Mission-3 Trajectories to a 9:2 NRHO Using Machine Learning
<p>The purpose of this thesis is to design a machine learning algorithm platform that provides expanded knowledge of mission availability through a launch season by improving trajectory resolution and introducing launch mission forecasting. The specific scenario addressed in this paper is one in …
-
Approaching Novel Perovskites Photovoltaic Devices through Machine Learning and Interfacial Engineering
… performance (etc. sputtered Ni). In addition, a machine learning algorithm is developed to predict the solar cell current-voltage properties only based on the film stack optical properties before the solar cell is fabricated. The algorithm is developed and tested based on the 3D/2D perovskite …
-
Happiness and Policy Implications: A Sociological View
… attempts to build from that base and create a machine learning algorithm that can predict if a country will be in a “happy” or “could be happier” category. Findings show that taking a broader scope of variables can better help predict happiness. Policy implications are discussed in using both …
-
Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters
In a world where Machine Learning Algorithms in the field of Image Processing is being developed at a rapid pace, a developer needs to have a better insight into all the algorithms to choose one among them for their application. When an algorithm is published, the developers of the algorithm …
Page 1 of 10