Sökning: "multidimensional optimization"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden multidimensional optimization.

1. 1. X-Ray Fluorescence of Metal Halide Perovskites

   Kandidat-uppsats, Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionen

   Författare :Samuel Narciso Silva; [2022]
   Nyckelord :Perovskite; X-ray; Fluorescence; Python; PyMCA; Synchrotron radiation; Physics and Astronomy;

   Sammanfattning : This thesis has the aim to provide a framework for analyzing X-ray fluorescence (XRF) data obtained from German Electron-Synchrotron Group (DESY). The theoretical analysis shows that XRF competes with Auger emission, and works mainly for elements with high atomic number. Here, incident X-rays of 13. LÄS MER

3. 2. Multi-dimensional Packing for Resource Allocation in 5G

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Matteo Ghetti; [2022]
   Nyckelord :;

   Sammanfattning : The Fifth Generation (5G) of wireless communication system brings a series of new challenges in resource optimization. For example optimizing the number of bits and dedicated time used by each service would improve the quality of communications. LÄS MER

4. 3. Optimization of event selection and fake background estimation in a search for heavy scalars in dilepton final states with the ATLAS detector

   Magister-uppsats, Lunds universitet/Partikel- och kärnfysik; Lunds universitet/Fysiska institutionen

   Författare :Marius Burman Ingeberg; [2021]
   Nyckelord :Physics; Particle physics; ATLAS; Standard Model; CERN; LHC; Higgs boson; Exotic Higgs Boson; Dilepton final states; Optimization; Physics and Astronomy;

   Sammanfattning : The discovery of the Higgs boson h in 2012 further confirmed the remarkable accuracy of the Standard Model (SM). Despite this, some compelling excesses in multi-lepton final states were recorded in both major runs of the Large Hadron Collider (LHC). LÄS MER

5. 4. Deep Learning for Dynamic Portfolio Optimization

   Master-uppsats, KTH/Matematisk statistik

   Författare :Victor Molnö; [2021]
   Nyckelord :Dynamic portfolio optimization; No-trade-region; Deep learning; Policy iteration; Dynamisk portföljoptimering; Handelsstoppregion; Djupinlärning; Policyiterering;

   Sammanfattning : This thesis considers a deep learning approach to a dynamic portfolio optimization problem. A proposed deep learning algorithm is tested on a simplified version of the problem with promising results, which suggest continued testing of the algorithm, on a larger scale for the original problem. LÄS MER

7. 5. Multitask Convolutional Neural Network Emulators for Global Crop Models - Supervised Deep Learning in Large Hypercubes of Non-IID Data

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Amanda Nilsson; [2020]
   Nyckelord :Multitask Learning; Convolutional Neural Network CNN ; Branched Neural Network; Dynamic Global Vegetation Models DGVM ; Automated Feature Extraction; Feature Importance; Supervised Machine Learning; Emulator; Surrogate Model; Response Surface Model; Approximation Model; Metamodeling; Model Composition; Regularization; Robustness; Hyperparameter Optimization; Mathematics and Statistics;

   Sammanfattning : The aim of this thesis is to establish whether a neural network (NN) can be used for emulation of simulated global crop production - retrieved from the computationally demanding dynamic global vegetation model (DGVM) Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS). It has been devoted to elaboration with various types of neural network architectures: Branched NNs capable of processing inputs of mixed data types; Convolutional Neural Network (CNN) architectures able to perform automated temporal feature extraction of the given weather time series; simpler fully connected (FC) structures as well as Multitask NNs. LÄS MER