Essays about: "long short term memory"
Showing result 16 - 20 of 334 essays containing the words long short term memory.
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16. Plant yield prediction in indoor farming using machine learning
University essay from Högskolan i Skövde/Institutionen för informationsteknologiAbstract : Agricultural industry has started to rely more on data driven approaches to improve productivity and utilize their resources effectively. This thesis project was carried out in collaboration with Ljusgårda AB, it explores plant yield prediction using machine learning models and hyperparameter tweaking. READ MORE
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17. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis
University essay from KTH/Matematik (Avd.)Abstract : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. READ MORE
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18. Artificial Neural Networks for Financial Time Series Prediction
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. READ MORE
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19. Assessing Electricity Prices and Their Driving Mechanisms in Brazil with Neural Networks
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : In general, electricity prices are very volatile and derive from many external variables. In Brazil, this price is determined by computer models developed and operated by government organizations. The supply and demand relationships are not enough to determine prices in Brazilian submarkets. READ MORE
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20. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
University essay from KTH/FysikAbstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE