Sökning: "Long ShortTerm Memory Neural Networks"

Hittade 5 uppsatser innehållade orden Long ShortTerm Memory Neural Networks.

1. 1. Demand Forecasting of Outbound Logistics Using Neural Networks

   Master-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Enobong Paul Otuodung; Gulten Gorhan; [2023]
   Nyckelord :Time Series Prediction; Demand Forecasting; Outbound Logistics; Machine Learning; Deep Learning; Univariate Forecasting; Multivariate Forecasting; Multi-Step Forecasting; LSTM; CNN-LSTM; ConvLSTM; Encoder-Decoder; Design science; Design science;

   Sammanfattning : Long short-term volume forecasting is essential for companies regarding their logistics service operations. It is crucial for logistic companies to predict the volumes of goods that will be delivered to various centers at any given day, as this will assist in managing the efficiency of their business operations. LÄS MER

3. 2. Punctuation Restoration as Post-processing Step for Swedish Language Automatic Speech Recognition

   Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Ishika Gupta; [2023]
   Nyckelord :Transformer; BERT; KB-BERT; NLP; punctuation restoration; deep learning; neural networks;

   Sammanfattning : This thesis focuses on the Swedish language, where punctuation restoration, especially as a postprocessing step for the output of Automatic Speech Recognition (ASR) applications, needs furtherresearch. I have collaborated with NewsMachine AB, a company that provides large-scale mediamonitoring services for its clients, for which it employs ASR technology to convert spoken contentinto text. LÄS MER

4. 3. Machine Learning to identify aberrant energy use to detect property failures

   Master-uppsats, KTH/Energiteknik

   Författare :Shahroz Habib; [2020]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

5. 4. Dynamic Student Embeddings for a Stable Time Dimension in Knowledge Tracing

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Clara Tump; [2020]
   Nyckelord :Knowledge Tracing; Exercise Recommendation; Adaptive Learning; Machine Learning; Word Embeddings; Dynamic Embeddings; Recurrent Neural Networks; Long Short-Term Memory Neural Networks; Kunskapsspårning; Uppgiftsrekommendation; Adaptivt Lärande; Maskininlärning; Ordvektorer; Dynamiska Studentvektorer; Recurrent Neural Networks; Long ShortTerm Memory Neural Networks;

   Sammanfattning : Knowledge tracing is concerned with tracking a student’s knowledge as she/he engages with exercises in an (online) learning platform. A commonly used state-of-theart knowledge tracing model is Deep Knowledge Tracing (DKT) which models the time dimension as a sequence of completed exercises per student by using a Long Short-Term Memory Neural Network (LSTM). LÄS MER

7. 5. Scalable System-Wide Traffic Flow Predictions Using Graph Partitioning and Recurrent Neural Networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jón Reginbald Ivarsson; [2018]
   Nyckelord :Traffic Flow Prediction; Machine Learning; Recurrent Neural Network; Graph Partitioning; Big Data; Trafikprognoser; Maskininlärning; Återkommande Neuralt Nätverk; Graf Partitionering; Big Data;

   Sammanfattning : Traffic flow predictions are an important part of an Intelligent Transportation System as the ability to forecast accurately the traffic conditions in a transportation system allows for proactive rather than reactive traffic control. Providing accurate real-time traffic predictions is a challenging problem because of the nonlinear and stochastic features of traffic flow. LÄS MER