Abstract Multi-Source Information Fusion (MSIF), as a comprehensive interdisciplinary field
based on modern information technology, has gained significant research value and …

Graphs are data structures that effectively represent relational data in the real world. Graph
representation learning is a significant task since it could facilitate various downstream …

Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …

The problem of air pollution threatens public health. Air quality forecasting can provide the
air quality index hours or even days later, which can help the public to prevent air pollution …

Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …

The increasing air pollution poses an urgent global concern with far-reaching
consequences, such as premature mortality and reduced crop yield, which significantly …

Air pollution constitutes a substantial peril to human health, thereby catalyzing the evolution
of an array of air quality prediction models. These models span from mechanistic and …

Predicting air quality using multimodal data is crucial to comprehensively capture the
diverse factors influencing atmospheric conditions. Therefore, this study introduces a …

Spatiotemporal forecasting has emerged as an indispensable building block of diverse
smart city applications, such as intelligent transportation and smart energy management …

Predicting present climate and the evolution of the ecosystem is more crucial than ever
because of the huge climatic shift that has occurred in nature. Weather forecasts normally …