Sökning: "Long Short-Term Memory Networks LSTM"

Visar resultat 11 - 15 av 141 uppsatser innehållade orden Long Short-Term Memory Networks LSTM.

1. 11. 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. 12. Temporal Localization of Representations in Recurrent Neural Networks

   Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

   Författare :Asadullah Najam; [2023]
   Nyckelord :Recurrent Neural Networks RNNs ; Deep Learning; Time Series Prediction; Exploding Values; Gradient Decay; Long Short-Term Memory LSTMs ; Gated Recurrent Units GRUs ; Attention Mechanism; Moving Representations; Localizing Representations;

   Sammanfattning : 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

4. 13. Local Planning for Unmanned Ground Vehicles using Imitation Learning

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

   Författare :Johan Henningsson; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : Mobile robotics is an expanding field worldwide leading to the need for advanced path-planning algorithms that can traverse various environments. Current state-ofthe- art path-planning algorithms used at the Swedish Defence Research Agency, FOI, tend to be inflexible and parameter dependent. LÄS MER

5. 14. Classifying personal data on contextual information

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

   Författare :Carl Dath; [2023]
   Nyckelord :Natural Language Processing; Machine Learning; Word2Vec; GloVe; BERT; Personal Data classification; Språkteknologi; Maskininlärning; Personlig Data Klassificering;

   Sammanfattning : In this thesis, a novel approach to classifying personal data is tested. Previous personal data classification models read the personal data before classifying it. However, this thesis instead investigates an approach to classify personal data by looking at contextual information frequently available in data sets. LÄS MER

7. 15. Latency Prediction in 5G Networks by using Machine Learning

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

   Författare :Erica Elgcrona; Evrim Mete; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : This thesis presents a report of predicting latency in a 5G network by using deep learning techniques. The training set contained data of network parameters along with the actual latency, collected in a 5G lab environment during four different test scenarios. LÄS MER