Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic s...

We present a Hidden Markov Model that uses qualitative order of magnitude probabilities for its states and transitions. We use the resulting model to construct a formalization of qualitative spatiotemporal events as random processes and utilize it to build high-level natural language description of change. We use the resulting model to show an example of foreseen usage of well-known prediction ...

This experiment illustrates the spatiotemporal pattern of the fluctuations that spontaneously develop in a magnetized temperature filament whose transverse scale is comparable to the electron skin depth. A high-frequency mode exhibits a striking spiral structure and is identified as a drift-Alfven eigenmode. A low-frequency mode is found to be localized near the center of the filament. It is do...

Partially-recurrent networks have advantages over strictly feed-forward networks for certain spatiotemporal pattern classification or prediction tasks. However networks involving recurrent links are generally more difficult to train than their nonrecurrent counterparts. In this paper we demonstrate that the costs of training a recurrent network can be greatly reduced by initialising the network...

in this paper, we review novel techniques in the emerging field of spatiotemporal 4d pet imaging. we will discuss existing limitations in conventional dynamic pet imaging which involves independent reconstruction of dynamic pet datasets. various approaches that seek to attempt some or all of these limitations are reviewed in this work, including techniques that utilize iterative temporal smooth...

The Asian monsoon system affects more than half of humanity worldwide, yet the dynamical processes that govern its complex spatiotemporal variability are not sufficiently understood to model and predict its behavior, due in part to inadequate long-term climate observations. Here we present the Monsoon Asia Drought Atlas (MADA), a seasonally resolved gridded spatial reconstruction of Asian monso...

Accurate and timely air quality weather predictions are of great importance to urban governance human livelihood. Though many efforts have been made for or prediction, most them simply employ one another as feature input, which ignores the inner-connection between two predictive tasks. On hand, accurate prediction task can help improve task's performance. other geospatially distributed monitori...

Existing traffic flow prediction methods generally only consider the spatiotemporal characteristics of flow. However, in addition to characteristics, interference various external factors needs be considered prediction, including severe weather, major events, control, and metro failures. The current research still cannot fully use information contained these factors. To address this issue, we p...