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**Description:**
Predicting future traffic flow, which will aid in traffic management and planning. The goal is to build a model that can accurately forecast traffic flow based on historical data a…
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We need to do the following during the planning stage:
- Create Architecture of Swetrix AI.
- Estimate the duration of the development.
- Spread tasks across the team.
- Define the stack to …
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Someone can explain to me how to make inference using a trained model using the code in timeseries_traffic_forecasting.py?
Imagine that a have historical data from 45 timesteps for 33 roads, and th…
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I got the following error when running the following example: [network_traffic_model_forecasting.ipynb](https://github.com/intel-analytics/analytics-zoo/blob/master/pyzoo/zoo/chronos/use-case/network_…
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- [ ] ARIMA
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Hello, as a novice in traffic flow forecasting and neural network, reading your paper helps me a lot. I hope to be able to reproduce your paper. Downloaded your code and cloud disk data, but still pro…
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## What's this paper about?
- Introduces 6 time series competitions held by Kaggle.
- Background: Real-life business forecasting tasks on Kaggle platform has been largely ignored by the academic …
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## Description
We should add the datasets mentioned in this paper https://www.researchgate.net/publication/339362837_Learnings_from_Kaggle's_Forecasting_Competitions to our library.
- [ ] Walmar…
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Darts has established itself as a premier time series forecasting library. Adding multi-horizon time series classification support would solidify its position and significantly benefit researchers and…
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This is the link towards github repo for the paper: -
Guo, S., Lin, Y., Feng, N., Song, C., & Wan, H. (2019, July). Attention based spatial-temporal graph convolutional networks for traffic flow for…