Sökning: "Black-box Optimization"

Visar resultat 21 - 25 av 29 uppsatser innehållade orden Black-box Optimization.

  1. 21. Learning-Based Auto-Tuning for Motion Controllers of Mobile Robots

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jonathan Blixt; [2019]
    Nyckelord :;

    Sammanfattning : An auto-tuner of the parameters of a mobile robots motion controlleris developed to improve its performance. The generality of the auto-tunerallows for similar applications on other robots or controllers. LÄS MER

  3. 22. Black-box optimization of simulated light extraction efficiency from quantum dots in pyramidal gallium nitride structures

    Master-uppsats, Linköpings universitet/Matematiska institutionen

    Författare :Karl-Johan Olofsson; [2019]
    Nyckelord :Black-box optimization; Radial basis functions; Gallium nitride; light extraction efficiency; FDTD; surrogate functions; semiconductors; global optimization;

    Sammanfattning : Microsized hexagonal gallium nitride pyramids show promise as next generation Light Emitting Diodes (LEDs) due to certain quantum properties within the pyramids. One metric for evaluating the efficiency of a LED device is by studying its Light Extraction Efficiency (LEE). LÄS MER

  4. 23. Finding Optimal Jetting Waveform Parameters with Bayesian Optimization

    Master-uppsats, KTH/Optimeringslära och systemteori

    Författare :Stefan Xueyan Fu; [2018]
    Nyckelord :;

    Sammanfattning : Jet printing is a method in surface mount technology (SMT) in which small volumes of solder paste or other electronic materials are applied to printed circuit boards (PCBs). The solder paste is shot onto the boards by a piston powered by a piezoelectric stack. LÄS MER

  5. 24. Application and Evaluation of Artificial Neural Networks in Solvency Capital Requirement Estimations for Insurance Products

    Master-uppsats, KTH/Matematisk statistik

    Författare :Mattias Nilsson; Erik Sandberg; [2018]
    Nyckelord :;

    Sammanfattning : The least squares Monte Carlo (LSMC) approach is commonly used in the estimation of the solvency capital requirement (SCR), as a more computationally efficient alternative to a full nested Monte Carlo simulation. This study compares the performance of artificial neural networks (ANNs) to that of the LSMC approach in the estimation of the SCR of various financial portfolios. LÄS MER

  7. 25. A Comparative Study of Black-box Optimization Algorithms for Tuning of Hyper-parameters in Deep Neural Networks

    Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för teknikvetenskap och matematik

    Författare :Skogby Steinholtz Olof; [2018]
    Nyckelord :;

    Sammanfattning : Deep neural networks (DNNs) have successfully been applied across various data intensive applications ranging from computer vision, language modeling, bioinformatics and search engines. Hyper-parameters of a DNN are defined as parameters that remain fixed during model training and heavily influence the DNN performance. LÄS MER