Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic
status are significant for economic development. The understanding of socioeconomic …

Traditional occupant behavior modeling has been studied at the building level, and it has
become an important factor in the investigation of building energy consumption. However …

Traffic congestion causes huge economic loss worldwide in every year due to wasted fuel,
excessive air pollution, lost time, and reduced productivity. Understanding how humans …

目的大数据时代的到来, 使得社会, 科学和经济都发生了巨大的变革. 当前,
基于各种测量传感网络来感知人类个体和群体与自然环境和社会环境关系的泛在测绘所产生的 …

Predicting the movement of crowds in a city is strategically important for traffic management,
risk assessment, and public safety. In this paper, we propose predicting two types of flows of …

The behaviour of building occupants in the first stage of an evacuation can dramatically
impact the time required to evacuate buildings. This behaviour has been widely investigated …

Event crowd management has been a significant research topic with high social impact.
When some big events happen such as an earthquake, typhoon, and national festival, crowd …

The frequency and intensity of natural disasters has significantly increased over the past
decades and this trend is predicted to continue. Facing these possible and unexpected …

Predicting the density and flow of the crowd or traffic at a citywide level becomes possible by
using the big data and cutting-edge AI technologies. It has been a very significant research …

Major disasters such as extreme weather events can magnify and exacerbate pre-existing
social disparities, with disadvantaged populations bearing disproportionate costs. Despite …