Sökning: "Spatial Dependencies"

Visar resultat 1 - 5 av 21 uppsatser innehållade orden Spatial Dependencies.

  1. 1. Spatial modeling with INLA for analysis of unequal care in Skåne

    Kandidat-uppsats, Lunds universitet/Matematisk statistik

    Författare :Julia Wierzchoslawska; [2023]
    Nyckelord :Mathematics and Statistics;

    Sammanfattning : The objective of this thesis is to extend on a previous analysis of health care accessibility for patients diagnosed with a chronic disease in Region Skåne. The previous analysis resulted in a logistic mixed effects model having municipality as a random effect and age as a first-degree spline-function. LÄS MER

  3. 2. Graph Neural Network for Traffic Flow Forecasting : Does an enriched adjacency matrix with low dimensional dataenhance the performance of GNN for traffic flow forecasting?

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Fredrik Kortetjärvi; Rohullah Khorami; [2023]
    Nyckelord :Graph Neural Network;

    Sammanfattning : Nowadays, machine learning methods are used in many applications and deployed in manyelectronic devices to solve problems and predict future states. One of the challenges mostbig cities confront is traffic jams since the roads are crammed with more and more vehicles, which will easily cause traffic congestion. LÄS MER

  4. 3. Geospatial Trip Data Generation Using Deep Neural Networks

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

    Författare :Aditya Deepak Udapudi; [2022]
    Nyckelord :Deep Learning; Geospatial; Generative Adversarial Network GAN ; Deep Learning; Geospatial; Generativa Motståndsnätverk GAN ;

    Sammanfattning : Development of deep learning methods is dependent majorly on availability of large amounts of high quality data. To tackle the problem of data scarcity one of the workarounds is to generate synthetic data using deep learning methods. LÄS MER

  5. 4. Generating Geospatial Trip DataUsing Deep Neural Networks

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Ahmed Alhasan; [2022]
    Nyckelord :Deep Learning; Machine Learning; Statistics; Generative Adversarial Networks; Computer Science; Generative Models;

    Sammanfattning : Synthetic data provides a good alternative to real data when the latter is not sufficientor limited by privacy requirements. In spatio-temporal applications, generating syntheticdata is generally more complex due to the existence of both spatial and temporal dependencies. LÄS MER

  7. 5. Data Trustworthiness Assessment for Traffic Condition Participatory Sensing Scenario

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

    Författare :Hairuo Gao; [2022]
    Nyckelord :Participatory sensing; Data trustworthiness assessment; Anomaly detection; Traffic prediction; Deep neural network; Deltagande avkänning; Bedömning av uppgifternas tillförlitlighet; Upptäckt av anomalier; Trafikprognoser; Djupt neuralt nätverk;

    Sammanfattning : Participatory Sensing (PS) is a common mode of data collection where valuable data is gathered from many contributors, each providing data from the user’s or the device’s surroundings via a mobile device, such as a smartphone. This has the advantage of cost-efficiency and wide-scale data collection. LÄS MER