Essays about: "moving networks"
Showing result 1 - 5 of 147 essays containing the words moving networks.
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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. Autonomous shuttle buses : A multiple-case study evaluating to what extent autonomous shuttle buses contribute to achieve sustainable mobility in Lindholmen and Barkarbystaden
University essay from Stockholms universitet/Kulturgeografiska institutionenAbstract : Travelling and moving within urban areas in a sustainable way acquires a transition toward sustainable commuting modes. An approach to reaching the transition is recognised as sustainable mobility. According to smart mobility research, autonomous shuttle buses could contribute to achieve sustainable mobility in urban areas. READ MORE
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3. Towards Circular Business Models in Swedish Rock and Soil Material Management : An Ecosystem-level Exploration
University essay from Linköpings universitet/Projekt, innovationer och entreprenörskapAbstract : The rapid growth of Swedish metropolitan regions, has led to increased demand for rock and soil materials for building construction and infrastructural work. Sweden's rock and soil material management industry extracts over 100 million tons of aggregate per year, while only succeeding in recycling 1% of it. READ MORE
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4. 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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5. 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