Sökning: "Vehicle Networks"

Visar resultat 1 - 5 av 223 uppsatser innehållade orden Vehicle Networks.

  1. 1. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Deepthy Prasad; Swathi Hampapura Sripada; [2023]
    Nyckelord :multivariate - time series; anomaly detection; neural networks; autoencoders; interpretability; counterfactuals;

    Sammanfattning : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. LÄS MER

  2. 2. Customizable Contraction Hierarchies for Mixed Fleet Vehicle Routing : Fast weight customization when not adhering to triangle inequality

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

    Författare :Martin Larsson; [2023]
    Nyckelord :Contraction Hierarchies; Customizable Contraction Hierarchies; Vehicle Routing Problem; Battery Electric Vehicles; Mixed Fleet; Kontraktionshierarkier; Anpassningsbara Kontraktionshierarkier; Ruttplanering; Batteridrivna elfordon; Blandad fordonsflotta;

    Sammanfattning : As the transport industry shifts towards Battery Electric Vehicles (BEVs) the need for accurate route planning rises. BEVs have reduced range compared to traditional fuel based vehicles, and the range can vary greatly depending on ambient conditions and vehicle load. LÄS MER

  3. 3. Implicit Message Integrity Provision : In Heterogeneous Vehicular Systems

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

    Författare :Paul Molloy; [2023]
    Nyckelord :Privacy; Code Generation; Vehicle-to-infrastructure; Vehicular ad hoc Networks; Standardization; Remote Procedure Calls; Safety; Integritet; Kodgenerering; Fordon-till-infrastruktur; Ad hoc-nät för Fordon; Standardisering; Samtal om fjärrprocedur; Säkerhet;

    Sammanfattning : Vehicles on the road today are complex multi-node computer networks. Security has always been a critical issue in the automotive computing industry. It is becoming even more crucial with the advent of autonomous vehicles and driver assistant technology. There is potential for attackers to control vehicles maliciously. LÄS MER

  4. 4. Lokalisering av borrhål i underjordsgruvor : Face drilling, del av adaptive automations projekt på Epiroc

    Master-uppsats, Örebro universitet/Institutionen för naturvetenskap och teknik

    Författare :Alex Melander; Edris Fatah; [2023]
    Nyckelord :;

    Sammanfattning : Yrkesmän har manuellt gjort borrplaner för varje borrsekvens, men denna modul med ett neuralt nätverk för punktmolnssegmentering- och- klassificering kommer att underlätta yrkesmännens behov genom att förenkla processen och utesluta orimliga delar i utgångsplanen. Dettaexamensarbete, som utförts i samarbete med Epiroc, en svensk tillverkare av gruv- och infrastrukturutrustning, fokuserar på att automatisera borrprocessen vid underjordisk gruvdrift. LÄS MER

  5. 5. Channel Estimation and Power Control Algorithms in the Presence of Channel Aging

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

    Författare :Yan Bixing; [2023]
    Nyckelord :Fading channel; auto-regressive model; power allocation; uncrewed aerial vehicle networks; Fading kanal; auto-regressiv modell; krafttilldelning; obemannade flygfordonsnätverk;

    Sammanfattning : Power allocation algorithms that determine how much power should be allocated to pilot and data symbols play an important role in addressing the trade-off between accurate channel estimation and high high spectral efficiency for data symbols in the presence of time-varying fading channels. Dealing with this trade-off is highly non-trivial when the channel changes or ages rapidly in time. LÄS MER