In recent years, artificial intelligence (AI) has been increasingly put into use to address cities'
economic, social, environmental, and governance challenges. Thanks to its advanced …

Predicting crime using machine learning and deep learning techniques has gained
considerable attention from researchers in recent years, focusing on identifying patterns and …

Predicting crimes before they occur can save lives and losses of property. With the help of
machine learning, many researchers have studied predicting crimes extensively. In this …

Abstract Land Surface Temperature (LST) is an important indicator of urban heat
environments and can be largely influenced by the morphology factors of cities. However …

Crime detection is one of the most important research applications in machine learning.
Identifying and reducing crime rates is crucial to developing a healthy society. Big Data …

Crime risk map plays a crucial role in urban planning and public security management.
Traditionally, it is obtained solely from historical crime incidents or inferred from limited …

Urban drought, a subtype of socio-economic drought, has received limited attention
compared to other types. Given the shifts in water supply patterns due to global climate …

The objective of crime prediction, one of the most important technologies in social
computing, is to extract useful information from many existing criminal records to predict the …

Abstract Machine learning techniques, such as random forest (RF), are increasingly utilized
in geographical studies, including crime analysis. While RF excels in predictive accuracy …

To promote the healthy development of cities, previous studies have long investigated the
relationships between urban functions and crime. However, the use of either land use data …