Sökning: "Non-linear"

Visar resultat 16 - 20 av 806 uppsatser innehållade ordet Non-linear.

  1. 16. Reinforcement learning for EV charging optimization : A holistic perspective for commercial vehicle fleets

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Enzo Alexander Cording; [2023]
    Nyckelord :Deep Reinforcement Learning; EV charging optimization; Artificial Intelligence; Commercial vehicle fleets; Electric vehicles; Deep Reinforcement Learning; optimering av elbilsladdning; artificiell intelligens; kommersiella fordonsflottor; Elektriska fordon;

    Sammanfattning : Recent years have seen an unprecedented uptake in electric vehicles, driven by the global push to reduce carbon emissions. At the same time, intermittent renewables are being deployed increasingly. These developments are putting flexibility measures such as dynamic load management in the spotlight of the energy transition. LÄS MER

  3. 17. Mapping of Dependent Structural Responses on a Prestressed Concrete Bridge using Machine Learning Regression Analysis and Historical Data : A Comparison of Different Non-linear Regression Approaches

    L1-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Vedad Coric; [2023]
    Nyckelord :Prestressed Concrete Bridges; Structural health Monitoring; Machine Learning; Regression analysis; Infrastructure management;

    Sammanfattning : Prestressed concrete bridges are susceptible to deterioration over time which might significantly affect their capacity and overall performance. In previous decades, infrastructure owners have found that continuous monitoring of these assets is a valuable tool for their management as it facilitates the decision-making process regarding the intervention strategies required. LÄS MER

  4. 18. A Machine Learning Approach on Analysis of Emission Spectra for Application in XFEL Experiments

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för fysik och astronomi

    Författare :Harald Agelii; [2023]
    Nyckelord :Structural biology; Machine learning; Neural networks; emission spectrum; XFEL; X-ray free electron laser; SFX; Serial femtosecond X-ray crystallography; Proteins; Diagnostics;

    Sammanfattning : In this thesis we investigate two potential applications of machine learning in the context of X-ray imaging and spectroscopy of biological samples, particularly such using X-ray free electron lasers (XFEL). We first investigate the possibility of using an emission spectrum, recorded from a sample after being probed by an incident X-ray, as a diagnostic tool. LÄS MER

  5. 19. Digital Front End Algorithms for Sub-Band Full Duplex

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Midhat Rizvi; Khaled Al-Khateeb; [2023]
    Nyckelord :Adjacent Channel Leakage Ratio; Bit Error Rate; Clipping and Filtering; Crest Factor Reduction; Digital front end; Digital Pre-Distortion Error Vector Magnitude; Frequency Division Duplex; Power Amplifier; Peak to Average Power Ratio; Peak Cancellation Crest Factor Reduction; Sub Band Full Duplex; Self-Interference Cancellation; Signal-to-Interference Noise Ratio; Signal-to-Noise Ratio; Turbo Clipping; Time Division Duplex; Technology and Engineering;

    Sammanfattning : Sub-band full duplex is a new communication scheme technology, where a single frequency band is partitioned into sub-bands for downlink (DL) and up-link(UL) transmissions, and both can take place simultaneously. The idea behind the sub-band full duplex development is to improve the throughput, and coverage and reduce the latency of the UL communication by allowing the UL reception during the DL transmission. LÄS MER

  7. 20. Can Machine Be a Good Stock Picker?: Bridging the Gap between Fundamental Data and Machine Learning

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Tomoya Narita; Povilas Stankevicius; [2023]
    Nyckelord :Machine Learning; XGBoost; Relative Valuation; Convergence Trade;

    Sammanfattning : We investigate the efficacy of historical accounting data and consensus forecasts for relative valuation of stocks, employing tree-based machine learning methods. We run an XGBoost model for monthly cross-sections of financial and pricing data of US equities from 1984 to 2021. LÄS MER