Sökning: "long short-term memory"
Visar resultat 11 - 15 av 340 uppsatser innehållade orden long short-term memory.
11. Machine Learning for State Estimation in Fighter Aircraft
Master-uppsats, KTH/Optimeringslära och systemteoriSammanfattning : This thesis presents an estimator to assist or replace a fighter aircraft’s air datasystem (ADS). The estimator is based on machine learning and LSTM neuralnetworks and uses the statistical correlation between states to estimate the angleof attack, angle of sideslip and Mach number using only the internal sensorsof the aircraft. LÄS MER
12. Aktiemarknadsprognoser: En jämförande studie av LSTM- och SVR-modeller med olika dataset och epoker
Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)Sammanfattning : Predicting stock market trends is a complex task due to the inherent volatility and unpredictability of financial markets. Nevertheless, accurate forecasts are of critical importance to investors, financial analysts, and stakeholders, as they directly inform decision-making processes and risk management strategies associated with financial investments. LÄS MER
13. Modelling Proxy Credit Cruves Using Recurrent Neural Networks
Master-uppsats, KTH/Matematisk statistikSammanfattning : Since the global financial crisis of 2008, regulatory bodies worldwide have implementedincreasingly stringent requirements for measuring and pricing default risk in financialderivatives. Counterparty Credit Risk (CCR) serves as the measure for default risk infinancial derivatives, and Credit Valuation Adjustment (CVA) is the pricing method used toincorporate this default risk into derivatives prices. LÄS MER
14. Predicting Cryptocurrency Prices with Machine Learning Algorithms: A Comparative Analysis
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: Due to its decentralized nature and opportunity for substantial gains, cryptocurrency has become a popular investment opportunity. However, the highly unpredictable and volatile nature of the cryptocurrency market poses a challenge for investors looking to predict price movements and make profitable investments. LÄS MER
15. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition
Master-uppsats, KTH/Mekatronik och inbyggda styrsystemSammanfattning : 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. LÄS MER