Urban crime prediction based on spatio-temporal Bayesian model

On Bayesian spatio-temporal modeling

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...

Spatio-Temporal Series Remote Sensing Image Prediction Based on Multi-Dictionary Bayesian Fusion

Contradictions in spatial resolution and temporal coverage emerge from earth observation remote sensing images due to limitations in technology and cost. Therefore, how to combine remote sensing images with low spatial yet high temporal resolution as well as those with high spatial yet low temporal resolution to construct images with both high spatial resolution and high temporal coverage has b...

Spatio-temporal analysis of the covid-19 impacts on the using Chicago urban shared bicycles by tensor-based approach

 Cycling is a phenomenon in urban transportation that has the ability to allocate a specific location at any moment in time. Accordingly, spatial analysis of bicycle trips can be accompanied by temporal analysis. The use of a GIS environment is commonly recommended to display the extent of the phenomenon's spatial changes. However, in order to apply and display changes over time, it will requir...

Spatio-Temporal Wildland Arson Crime Functions

Wildland arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p) model, is estimated for six high arson Census tracts in the stat...