Essays about: "probabilistic method"

Showing result 1 - 5 of 116 essays containing the words probabilistic method.

  1. 1. Data-Driven Reachability Analysis of Pedestrians Using Behavior Modes : Reducing the Conservativeness in Data-Driven Pedestrian Predictions by Incorporating Their Behavior

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : August Söderlund; [2023]
    Keywords : Data-driven reachability analysis; Autonomous vehicles; Automated safety; Autonomous situational awareness; Datadriven nåbarhetsanalys; Autonoma fordon; Automatiserad säkerhet; Autonom situationsmedvetenhet;

    Abstract : Predicting the future state occupancies of pedestrians in urban scenarios is a challenging task, especially considering that conventional methods need an explicit model of the system, hence introducing data-driven reachability analysis. Data-driven reachability analysis uses data, inherently produced by an unknown system, to perform future state predictions using sets, generally represented by zonotopes. READ MORE

  3. 2. Probabilistic Added Wave Resistance Predictions for Design of RoPax Ferries

    University essay from KTH/Lättkonstruktioner, marina system, flyg- och rymdteknik, rörelsemekanik

    Author : Jonathan Viinikka; [2023]
    Keywords : Added wave resistance in head waves; Roll-on Roll-off Passenger ferry; Probabilistic wave environment; Semi-empirical method; Adderat vågmotstånd i motsjö; Roll-on Roll-off Passagerar Fartyg; Probabilistiska vågförhållanden; Semiempiriska beräkningsmethoder;

    Abstract : This thesis investigates reasons for significant uncertainties in added wave resistance predictionsand how wave conditions can potentially affect the design of RoPax ferries. The objectiveis to find a suitable prediction method of added wave resistance for the RoPax ferry designapplication. READ MORE

  4. 3. Transmission expansion planning considering Probabilistic Risk Assessment : Implemented at Swedish National Grid

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Jakob Björns; [2023]
    Keywords : Probabilistic risk assessment; PSS E; Transmission expansion planning; National grid; Probabilistisk riskbedömning; PSS E; Transmissionsnätsutveckling; Stamnät;

    Abstract : Svenska kraftnät (Swedish National Grid) is the transmission system operator in Sweden and is responsible for maintaining and developing the Swedish transmission grid. One of the tasks included in this responsibility is transmission expansion planning, which means analyzing and planning the capacity in the future transmission grid for the requested load and generation. READ MORE

  5. 4. Constructing and representing a knowledge graph(KG) for Positive Energy Districts (PEDs)

    University essay from Högskolan Dalarna/Institutionen för information och teknik

    Author : Mahtab Davari; [2023]
    Keywords : Knowledge graph; Positive Energy Districts PEDs ; longest path; Questions and Answers; Community Detection; Node Embedding; t-SNE plots; Edge Prediction;

    Abstract : In recent years, knowledge graphs(KGs) have become essential tools for visualizing concepts and retrieving contextual information. However, constructing KGs for new and specialized domains like Positive Energy Districts (PEDs) presents unique challenges, particularly when dealing with unstructured texts and ambiguous concepts from academic articles. READ MORE

  6. 5. Generation of Synthetic Traffic Sign Images using Diffusion Models

    University essay from Linköpings universitet/Datorseende

    Author : Johanna Carlson; Lovisa Byman; [2023]
    Keywords : Machine Learning; Computer Vision; Diffusion Models; Traffic Sign Recognition; Traffic Sign Classification; Synthetic Data; Maskininlärning; Datorseende; Diffusionsmodeller; Trafikskyltsigenkänning; Trafikskyltsklassificering; Syntetisk data;

    Abstract : In the area of Traffic Sign Recognition (TSR), deep learning models are trained to detect and classify images of traffic signs. The amount of data available to train these models is often limited, and collecting more data is time-consuming and expensive. READ MORE