Essays about: "nätverk statistik"

Showing result 1 - 5 of 115 essays containing the words nätverk statistik.

1. 1. Modelling Proxy Credit Cruves Using Recurrent Neural Networks

   University essay from KTH/Matematisk statistik

   Author : Lucas Fageräng; Hugo Thoursie; [2023]
   Keywords : Deep Neural Networks; Credit Risk; Financial Modelling; LSTM; Credit Default Swaps; Credit Valuation Adjustment; Djupa Neurala Nätverk; Kreditrisk; Finansiell Modellering; LSTM; Kreditswappar; Kreditvärderingsjustering;

   Abstract : 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. READ MORE

3. 2. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction

   University essay from KTH/Matematisk statistik

   Author : Sabina Syed; Josefin Stenberg; [2023]
   Keywords : Adversarial Convex Regularization; Computer Vision; Cone Beam Computed Tomography; Convolutional Neural Networks; Deep Learning; Image Reconstruction; Adversarial Convex Regularization; Bildrekonstruktion; Datorseende; Djupinlärning; Faltningsnätverk; Volymtomografi;

   Abstract : Cone Beam Computed Tomography is a technology to visualize the 3D interior anatomy of a patient. It is important for image-guided radiation therapy in cancer treatment. During a scan, iterative methods are often used for the image reconstruction step. READ MORE

4. 3. AI Based Methods for Matrix Multiplication in High Resolution Simulations of Radio Access Networks

   University essay from KTH/Matematisk statistik

   Author : Marcus Johnson; Herman Forslund; [2023]
   Keywords : Product-Quantization; MADDNESS; Radio Access Networks; Channel Estimation; MIMO; Approximate Matrix Multiplication; Pruduktkvantisering; MADDNESS; RAN; MIMO; Approximativa matrismultiplikation;

   Abstract : The increasing demand for mobile data has placed significant strain on radio access networks (RANs), leading to a continuous need for increased network capacity. In keeping with that, a significant advancement in modern RANs is the ability to utilize several receivers and transmitters, to allow for beamforming. READ MORE

5. 4. Segment Routing Based Traffic Engineering : A QoS adaptive rerouting using segment routing approach based on IPv6 to mitigate network congestion

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Sepehr Javid; [2023]
   Keywords : Segment Routing with IPv6; Quality of Service; Congestion; Extended Berkeley Packet Filter; Segmentering av vägval med IPv6; Tjänstekvalitet; Överbelastning; Utökad Berkeley Packet Filter;

   Abstract : In modern networks, the increasing volume of network traffic and the diverse range of services with varying requirements necessitate the implementation of more advanced routing decisions and traffic engineering. This academic study proposes a QoS adaptive mechanism called "Sepitto", which utilizes Segment routing protocols, specifically SRv6, to address network-traffic control and congestion avoidance. READ MORE

6. 5. Portfolio Risk Modelling in Venture Debt

   University essay from KTH/Matematisk statistik

   Author : John Eriksson; Jacob Holmberg; [2023]
   Keywords : Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

   Abstract : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. READ MORE