Sökning: "Time-series prediction"
Visar resultat 16 - 20 av 237 uppsatser innehållade orden Time-series prediction.
16. Time Series Anomaly Detection in Radio Test
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Production tests evaluate products with automated systems enabling swift data collection, while anomaly detection in the gathered data is widely employed in industries for damage prediction and issue prevention. Ericsson, a leader in the telecommunications industry, has a Temperature Quality Test (TQT) platform which involves precise performance measurements on radios, gathering abundant data in both single value and time series formats to evaluate and improve tested products. LÄS MER
17. Temporal Localization of Representations in Recurrent Neural Networks
Master-uppsats, Högskolan Dalarna/Institutionen för information och teknikSammanfattning : Recurrent Neural Networks (RNNs) are pivotal in deep learning for time series prediction, but they suffer from 'exploding values' and 'gradient decay,' particularly when learning temporally distant interactions. Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) have addressed these issues to an extent, but the precise mitigating mechanisms remain unclear. LÄS MER
18. A Transformer-Based Scoring Approach for Startup Success Prediction : Utilizing Deep Learning Architectures and Multivariate Time Series Classification to Predict Successful Companies
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The Transformer, an attention-based deep learning architecture, has shown promising capabilities in both Natural Language Processing and Computer Vision. Recently, it has also been applied to time series classification, which has traditionally used statistical methods or the Gated Recurrent Unit (GRU). LÄS MER
19. Inferring Gene regulatory networks using Graph Neural Networks
Master-uppsats, KTH/GenteknologiSammanfattning : Inom beräkningsbiologin är det snabbt på väg att bli allt vanligare att ta fram genetiska regleringsnätverk (GRN). På grund av storleken på de undersökta nätverken använder många forskare maskininlärning för att härleda GRN från genuttrycksdata, vanligtvis från RNA-seq. LÄS MER
20. Neural Network-Based Residential Water End-Use Disaggregation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Sustainable management of finite resources is vital for ensuring livable conditions for both current and future generations. Measuring the total water consumption of residential households at high temporal resolutions and automatically disaggregating the sole signal into classified end usages (e.g. LÄS MER