Essays about: "arima models"
Showing result 1 - 5 of 92 essays containing the words arima models.
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1. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks
University essay from Uppsala universitet/Statistiska institutionenAbstract : Due to the growing share of renewable energy in countries' power systems, the need for precise forecasting of electricity consumption will increase. This paper considers two different approaches to time series forecasting, autoregressive moving average (ARMA) models and recurrent neural networks (RNNs). READ MORE
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2. Demand Forecasting of Automobile Spare Parts after the End-of-Production - A review of demand forecasting models
University essay from Göteborgs universitet/Graduate SchoolAbstract : Demand forecasting of spare parts plays a crucial role in automobile industry where it generally requires a significant attention in controlling inventory. It is possible to maintain an optimal stock level when there is a continues supply at the Original Equipment Manufacturers (OEMs). READ MORE
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3. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. READ MORE
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4. On modelling OMXS30 stocks - comparison between ARMA models and neural networks
University essay from Uppsala universitet/Matematiska institutionenAbstract : This thesis compares the results of the performance of the statistical Autoregressive integrated moving average (ARIMA) model and the neural network Long short-term model (LSTM) on a data set, which represents a market index. Both models are used to predict monthly, daily, and minute close prices of the OMX Stockholm 30 Index. READ MORE
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5. 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
