Sökning: "kernel ridge regression"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden kernel ridge regression.

1. 1. Kernel Methods for Regression

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för matematik (MA)

   Författare :Tom Lennart Rossmann; [2023]
   Nyckelord :Kernel Methods; Regression; Ridge Regression;

   Sammanfattning : Kernel methods are a well-studied approach for addressing regression problems by implicitly mapping input variables into possibly infinite-dimensional feature spaces, particularly in cases where standard linear regression fails to capture non-linear relationships in data. Therefore, the choice between standard linear regression and kernel regression can be seen as a tradeoff between constraints on the number of features and the number of training samples. LÄS MER

3. 2. HRTF-Based Sound Field Interpolation in the Presence of a Human Head

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Anton Björkman; [2023]
   Nyckelord :Sound field interpolation; HRTF; head-related transfer function; kernel ridge regression; in-ear sound estimate; Helmholtz equation; Mathematics and Statistics;

   Sammanfattning : There are different ways of evaluating the sound pressure in a sound field. Doing so is an essential part of several applications, such as active sound control and voice analysis. LÄS MER

4. 3. Predicting Reactor Instability Using Neural Networks

   Kandidat-uppsats, KTH/Fysik

   Författare :Hilborn Hubert; [2022]
   Nyckelord :Boiling Water Reactors; Density Wave Instability; Multi-Layer Perceptron; Support Vector Regression; Kernel-Ridge Regression;

   Sammanfattning : The study of the instabilities in boiling water reactors is of significant importance to the safety withwhich they can be operated, as they can cause damage to the reactor posing risks to both equipmentand personnel. The instabilities that concern this paper are progressive growths in the oscillatingpower of boiling-water reactors. LÄS MER

5. 4. Modelling Magnetism of hcp Iron under Earth’s Inner Core Conditions : Based on first-principle DFT calculations and Machine Learning

   Master-uppsats, Linköpings universitet/Teoretisk Fysik

   Författare :Linda Le; [2022]
   Nyckelord :Machine learning; Earth’s Inner Core; hcp Iron; Electronic structure magnetism; Density functional Theory; Local magnetic moments; Ab initio molecular dynamics; ASD-AIMD-MLLSF simulation;

   Sammanfattning : The structure of Earth’s core remains largely a mystery. The solid inner core is believed to exist in extreme pressure and temperature conditions comparable to 300 GPa and 6000 K and consists mainly of iron, Fe. LÄS MER

7. 5. Accelerating bulk material property prediction using machine learning potentials for molecular dynamics : predicting physical properties of bulk Aluminium and Silicon

   Master-uppsats, Linköpings universitet/Teoretisk Fysik

   Författare :Nicholas Sepp Löfgren; [2021]
   Nyckelord :machine learning; moment tensor potential; kernel ridge regression; molecular dynamics; density functional theory; materials science; data-driven materials design; maskininlärning; molekylärdynamik; täthetsfunktionalteori; materialvetenskap; datadriven materialdesign;

   Sammanfattning : In this project machine learning (ML) interatomic potentials are trained and used in molecular dynamics (MD) simulations to predict the physical properties of total energy, mean squared displacement (MSD) and specific heat capacity for systems of bulk Aluminium and Silicon. The interatomic potentials investigated are potentials trained using the ML models kernel ridge regression (KRR) and moment tensor potentials (MTPs). LÄS MER