Sökning: "output error method"

Visar resultat 1 - 5 av 101 uppsatser innehållade orden output error method.

1. 1. The Role of Uni- and Multivariate Bias Adjustment Methods for Future Hydrological Projections and Subsequent Decision-Making

   Master-uppsats, Uppsala universitet/Luft-, vatten- och landskapslära

   Författare :Anna Merle Liebenehm-Axmann; [2024]
   Nyckelord :Bias adjustment methods; future hydrological climate projections; statistical analysis; future streamflow analysis; biasjusteringsmetoder; framtida hydrologiska projektioner; statistisk analys; framtida vattenförings analys;

   Sammanfattning : Climate models are essential for generating future climate projections. However, due to simplifications, the models can produce systematic differences between output and reality, which is referred to as model bias. Bias adjustment methods aim to reduce this error, which is important for making future projections more reliable. LÄS MER

3. 2. Performance metrics and velocity influence for point cloud registration in autonomous vehicles

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Óscar Poveda Ruiz; [2023]
   Nyckelord :autonomous vehicle; localization; registration; metrics; error; classification; estimation; autonomt fordon; lokalisering; registrering; mätvärden; fel; klassificering; uppskattning;

   Sammanfattning : Autonomous vehicles are currently under study and one of the critical parts is the localization of the vehicle in the environment. Different localization methods have been studied over the years, such as the GPS sensor, commonly fused with other sensors such as the IMU. LÄS MER

4. 3. Telemetry for Debugging Software Issues in Privacy-sensitive Systems

   Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :Kasper Landgren; Payam Tavakoli; [2023]
   Nyckelord :telemetry; privacy; distributed tracing; debugging; privacy-sensitive system; tracing;

   Sammanfattning : Traditionally, when debugging a software system, developers rely on having access to the input data that caused the error. However, with data privacy concerns on the rise, it is becoming increasingly challenging to rely on input data as it might be sensitive or even classified. LÄS MER

5. 4. A Machine Learning Approach on Analysis of Emission Spectra for Application in XFEL Experiments

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för fysik och astronomi

   Författare :Harald Agelii; [2023]
   Nyckelord :Structural biology; Machine learning; Neural networks; emission spectrum; XFEL; X-ray free electron laser; SFX; Serial femtosecond X-ray crystallography; Proteins; Diagnostics;

   Sammanfattning : In this thesis we investigate two potential applications of machine learning in the context of X-ray imaging and spectroscopy of biological samples, particularly such using X-ray free electron lasers (XFEL). We first investigate the possibility of using an emission spectrum, recorded from a sample after being probed by an incident X-ray, as a diagnostic tool. LÄS MER

7. 5. Deep Neural Networks as SurrogateModels for Fuel Performance Codes

   Kandidat-uppsats, Uppsala universitet/Tillämpad kärnfysik

   Författare :Wenhan Zhou; [2023]
   Nyckelord :Transuranus; AI; Nuclear Fuel Rods;

   Sammanfattning : The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. LÄS MER