Essays about: "Spatial Dependencies"
Showing result 1 - 5 of 20 essays containing the words Spatial Dependencies.
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1. Spatial modeling with INLA for analysis of unequal care in Skåne
University essay from Lunds universitet/Matematisk statistikAbstract : 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. READ MORE
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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?
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : 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. READ MORE
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3. Geospatial Trip Data Generation Using Deep Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE
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4. Generating Geospatial Trip DataUsing Deep Neural Networks
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : 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. READ MORE
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5. Data Trustworthiness Assessment for Traffic Condition Participatory Sensing Scenario
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE