Essays about: "Anomalidetektering"
Showing result 16 - 20 of 29 essays containing the word Anomalidetektering.
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16. Online Anomaly Detection on the Edge
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The society of today relies a lot on the industry and the automation of factory tasks is more prevalent than ever before. However, the machines taking on these tasks require maintenance to continue operating. This maintenance is typically given periodically and can be expensive while sometimes requiring expert knowledge. READ MORE
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17. EVALUATION OF UNSUPERVISED MACHINE LEARNING MODELS FOR ANOMALY DETECTION IN TIME SERIES SENSOR DATA
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the advancement of the internet of things and the digitization of societies sensor recording time series data can be found in an always increasing number of places including among other proximity sensors on cars, temperature sensors in manufacturing plants and motion sensors inside smart homes. This always increasing reliability of society on these devices lead to a need for detecting unusual behaviour which could be caused by malfunctioning of the sensor or by the detection of an uncommon event. READ MORE
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18. Machine Learning to identify aberrant energy use to detect property failures
University essay from KTH/EnergiteknikAbstract : The digitalization of energy sector has provided immense amount of data about buildings which created an untapped opportunity for energy savings using energy data analytics. In recent years, there has been significant research on energy optimization using machine learning. READ MORE
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19. Automated advanced analytics on vehicle data using AI
University essay from KTH/FordonsdynamikAbstract : The evolution of electrification and autonomous driving on automotive leads to the increasing complexity of the in-vehicle electrical network, which poses a new challenge for testers to do troubleshooting work in massive log files. This thesis project aims to develop a predictive technique for anomaly detection focusing on user function level failures using machine learning technologies. READ MORE
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20. Anomaly Detection in Time Series Data using Unsupervised Machine Learning Methods: A Clustering-Based Approach
University essay from KTH/Matematisk statistikAbstract : For many companies in the manufacturing industry, attempts to find damages in their products is a vital process, especially during the production phase. Since applying different machine learning techniques can further aid the process of damage identification, it becomes a popular choice among companies to make use of these methods to enhance the production process even further. READ MORE