Essays about: "Time Series Prediction"
Showing result 11 - 15 of 242 essays containing the words Time Series Prediction.
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11. CryptoCurrency Time Series analysis : Comparative analysis between LSTM and BART Algorithm
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: Cryptocurrency is an innovative digital or virtual form of money thatuses cryptographic techniques for secured financial transactions within a decentralized structure. Due to its high volatility and susceptibility to external factors, itis difficult to understand its behavior which makes accurate predictions challengingfor the investors who are trying to forecast price changes and make profitable investments. READ MORE
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12. Air quality prediction in metropolitan areas using deep learning methods
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : The rapid growth of the world's urban population shows that people are increasingly moving to cities. In recent decades, the frequent occurrence of smog caused by increasing industrialization has brought environmental pollution to record highs. READ MORE
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13. Demand Forecasting of Outbound Logistics Using Neural Networks
University essay from Malmö universitet/Fakulteten för teknik och samhälle (TS)Abstract : 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. READ MORE
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14. Applying unprocessed companydata to time series forecasting : An investigative pilot study
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Demand forecasting for sales is a widely researched topic that is essential for a business to prepare for market changes and increase profits. Existing research primarily focus on data that is more suitable for machine learning applications compared to the data accessible to companies lacking prior machine learning experience. READ MORE
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15. A Mixed Time-Series & Machine Learning Approach for Price Forecasting in the Swedish Ancillary Market
University essay from Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionenAbstract : This study aims to forecast the Swedish FCR-D Down A2 market prices through a hybrid model combining a volatility model and a machine learning approach, and compares its performance with a standalone machine learning model. We further examine the impact of different lag orders (1-Hr vs. 24-Hr) on volatility estimates and forecast performance. READ MORE