Dynamic graph convolutional networks with Temporal representation learning for traffic flow prediction
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DOI: 10.1038/s41598-025-01696-7
Abstract: In the realm of traffic prediction, emerging are methodologies founded on graph convolutional networks. Nonetheless, existing approaches grapple with issues encompassing insufficient sharing patterns, dependence on static relationship presumptions, and an inability to effectively grasp… read more here.
Keywords: temporal representation; graph convolutional; traffic flow; dynamic graph ... See more keywords
Application of State Models in a Binary–Temporal Representation for the Prediction and Modelling of Crude Oil Prices
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DOI: 10.3390/en18030691
Abstract: Crude oil prices have a key meaning for the economies of most countries. Their levels shape the general production costs in many sectors. Oil prices are also a base for financial derivatives like CFD contracts,… read more here.
Keywords: temporal representation; crude oil; oil prices; binary temporal ... See more keywords
Algorithmic Trading System with Adaptive State Model of a Binary-Temporal Representation
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DOI: 10.3390/risks13080148
Abstract: In this paper a new state model is introduced, an adaptative state model in a binary temporal representation (ASMBRT) as well as its application in constructing an algorithmic trading system. The presented model uses the… read more here.
Keywords: temporal representation; algorithmic trading; state model; model ... See more keywords