scholarly journals Local and Global Iterative Algorithms for Real-Time Short-Term Traffic Prediction

10.5772/10178 ◽  
2010 ◽  
Author(s):  
Eleni Vlahogianni ◽  
Matthew Karlaftis
Keyword(s):  
Real Time ◽  
Iterative Algorithms ◽  
Traffic Prediction ◽  
Short Term

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

Nowcasting global trade in goods and services

2020 ◽  
pp. 1-19
Author(s):  
Fernando Cantú-Bazaldúa
Keyword(s):  
Real Time ◽  
Relevant Information ◽  
Global Trade ◽  
Dynamic Factor ◽  
Timely Manner ◽  
Short Term ◽  
Dynamic Factor Models ◽  
Significant Information ◽  
Goods And Services ◽  
World Economic

World economic aggregates are compiled infrequently and released after considerable lags. There are, however, many potentially relevant series released in a timely manner and at a higher frequency that could provide significant information about the evolution of global aggregates. The challenge is then to extract the relevant information from this multitude of indicators and combine it to track the real-time evolution of the target variables. We develop a methodology based on dynamic factor models adapted for variables with heterogeneous frequencies, ragged ends and missing data. We apply this methodology to nowcast global trade in goods in goods and services. In addition to monitoring these variables in real time, this method can also be used to obtain short-term forecasts based on the most up-to-date values of the underlying indicators.

scholarly journals Transferability improvement in short-term traffic prediction using stacked LSTM network

2021 ◽  
Vol 124 ◽  
pp. 102977
Author(s):  
Junyi Li ◽  
Fangce Guo ◽  
Aruna Sivakumar ◽  
Yanjie Dong ◽  
Rajesh Krishnan
Keyword(s):  
Traffic Prediction ◽  
Short Term ◽  
Lstm Network

scholarly journals Short-term Traffic Prediction with Deep Neural Networks: A Survey

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Kyungeun Lee ◽  
Moonjung Eo ◽  
Euna Jung ◽  
Yoonjin Yoon ◽  
Wonjong Rhee
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Traffic Prediction ◽  
Short Term
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