Sökning: "Parametric Programming"
Visar resultat 1 - 5 av 20 avhandlingar innehållade orden Parametric Programming.
1. Models of Surface Roughness with Applications in Paper Industry
Sammanfattning : This thesis comprises general parametric models for surface roughness. The models can be used in several technical and natural applications but are here only applied to the micro-structure of paper. In that application, earlier models are generalized and new models introduced. LÄS MER
2. Structure-Exploiting Numerical Algorithms for Optimal Control
Sammanfattning : Numerical algorithms for efficiently solving optimal control problems are important for commonly used advanced control strategies, such as model predictive control (MPC), but can also be useful for advanced estimation techniques, such as moving horizon estimation (MHE). In MPC, the control input is computed by solving a constrained finite-time optimal control (CFTOC) problem on-line, and in MHE the estimated states are obtained by solving an optimization problem that often can be formulated as a CFTOC problem. LÄS MER
3. Road profile statistics relevant for vehicle fatigue
Sammanfattning : Road profiles are studied from a vehicle fatigue point of view. A wide range of roads have been measured: from smooth motorways to very rough gravel roads. It is observed that the road profiles consist of irregular sections, which makes the stationary Gaussian model unsuitable (Paper A). LÄS MER
4. Pointwise and Genomewide Significance Calculations in Gene Mapping through Nonparametric Linkage Analysis: Theory, Algorithms and Applications
Sammanfattning : In linkage analysis or, in a wider sense, gene mapping one searches for disease loci along a genome. This is done by observing so called marker genotypes (alleles) and phenotypes (affecteds/unaffecteds) of a pedigree set, i.e. LÄS MER
5. Offline and Online Models for Learning Pairwise Relations in Data
Sammanfattning : Pairwise relations between data points are essential for numerous machine learning algorithms. Many representation learning methods consider pairwise relations to identify the latent features and patterns in the data. This thesis, investigates learning of pairwise relations from two different perspectives: offline learning and online learning. LÄS MER