Sökning: "Ordinary Differential Equation"
Visar resultat 1 - 5 av 27 uppsatser innehållade orden Ordinary Differential Equation.
1. An agent-based model approach to computational epidemiology
Kandidat-uppsats, KTH/DatavetenskapSammanfattning : The aim of this work was to compare different Non-pharmaceutical interventions (NPIs) in a simulated environment modeling Sweden with 10 000 000 (ten million) agents. Simulating the performance of these NPIs can be beneficial to policymakers and other government officials in order to give the power to make the right decision in the face of an epidemic. LÄS MER
2. Modelling and Simulation of Complete Wheel Loader in Modelica : Evaluation using Modelon Impact software
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Modelling and simulation of complex and multi-domain mechanical systems has become of major importance in the last few years to address energy and fuel consumption performance evaluation. The goal is to unify the available modelling languages aiming to improve scalability and easiness of handling complex multi-domain models. LÄS MER
3. Numeriska fouriertransformen och dess användning : En introduktion
Kandidat-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakultetenSammanfattning : The aim of this bachelor's thesis is to use three variants of the discrete Fourier transform (DFT) and compare their computational cost. The transformation will be used to numerically solve partial differential equations (PDE). In its simplest form, the DFT can be regarded as a matrix multiplication. LÄS MER
4. Parameter estimation in a cardiovascular computational model using numerical optimization : Patient simulation, searching for a digital twin
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Developing models of the cardiovascular system that simulates the dynamic behavior of a virtual patient’s condition is fundamental in the medical domain for predictive outcome and hypothesis generation. These models are usually described through Ordinary Differential Equation (ODE). LÄS MER
5. Physics-informed Neural Networks for Biopharma Applications
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysikSammanfattning : Physics-Informed Neural Networks (PINNs) are hybrid models that incorporate differential equations into the training of neural networks, with the aim of bringing the best of both worlds. This project used a mathematical model describing a Continuous Stirred-Tank Reactor (CSTR), to test two possible applications of PINNs. LÄS MER