Essays about: "Recurrent Neural network RNN"
Showing result 1 - 5 of 93 essays containing the words Recurrent Neural network RNN.
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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. Time Series Forecasting on Database Storage
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Time Series Forecasting has become vital in various industries ranging from weather forecasting to business forecasting. There is a need to research database storage solutions for companies in order to optimize resource allocation, enhance decision making process and enable predictive data storage maintenance. READ MORE
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3. Object Recognition in Satellite imagesusing improved ConvolutionalRecurrent Neural Network
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background:The background of this research lies in detecting the images from satellites. The recognition of images from satellites has become increasingly importantdue to the vast amount of data that can be obtained from satellites. This thesisaims to develop a method for the recognition of images from satellites using machinelearning techniques. READ MORE
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4. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition
University essay from KTH/Mekatronik och inbyggda styrsystemAbstract : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. READ MORE
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5. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE