The study of urban dynamics is to understand and analyse the dynamic properties of a city in the spatio-temporal domain. It includes the daily routines of the inhabitants, their movement patterns, g

Multivariate time series (MTS) prediction plays a significant role in many practical data mining applications, such as finance, energy supply, and medical care domains. Over the years, various predi

The travelling officer problem (TOP) is a graph-based orienteering problem for modelling the patrolling routines of a parking officer monitoring an area. Recently, a spatiotemporal probabilistic mo

The smart parking system is one of the most important problems in smart cities. Recently, an increasing number of sensors installed in parking spaces provide big spatio-temporal data which be used

The Travelling Officer Problem (TOP) is a graph-based orienteering problem for modelling the patrolling routines of a parking officer monitoring an area. Recently, a spatiotemporal probabilistic m

Deep learning has been extended to a number of new domains with critical success, though some traditional orienteering problems such as the Travelling Salesman Problem (TSP) and its variants are

Finding the shortest route between a pair of origin and destination is known to be a crucial and challenging task in intelligent transportation systems. Current methods assume fixed travel time be