Sökning: "long short-term memory LSTM"
Visar resultat 21 - 25 av 264 uppsatser innehållade orden long short-term memory LSTM.
21. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
Master-uppsats, KTH/FysikSammanfattning : 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). LÄS MER
22. Demand Forecasting of Outbound Logistics Using Neural Networks
Master-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)Sammanfattning : Long short-term volume forecasting is essential for companies regarding their logistics service operations. It is crucial for logistic companies to predict the volumes of goods that will be delivered to various centers at any given day, as this will assist in managing the efficiency of their business operations. LÄS MER
23. Classifying Motion Patterns of Bikes using Machine Learning
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknikSammanfattning : Electric bikes have become ubiquitous in traffic, and with a growing user base and expensive prices, a demand for bike protection is increasing. Bike protection applications could include detecting and notifying the owner if their bike has been stolen or fallen over. LÄS MER
24. Data Driven Modeling for Aerodynamic Coefficients
Master-uppsats, KTH/Matematisk statistikSammanfattning : Accurately modeling aerodynamic forces and moments are crucial for understanding thebehavior of an aircraft when performing various maneuvers at different flight conditions.However, this task is challenging due to complex nonlinear dependencies on manydifferent parameters. LÄS MER
25. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. LÄS MER