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I have traffic jam intensity of many location in different times of eabch day. So I have kind of 3D data, where the intensities in each location is 2D like an image. Then there is time as a third dimension.

Now, I want to predict traffic jam intensity at a give location and time. The intensity is from 0.0 to 10.0. high the intensity means high traffic jam.

Example. Whats the jam intensity of X latitude and Y longitude on 3:45 PM?

My question is how to feed that 3D data to my neural network?

NB: both the time and location contextual data. The intensity of the traffic jam is behavioral.

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    $\begingroup$ Any chance of seeing one or two of these traffic intensity maps? $\endgroup$
    – Spacedman
    Apr 20, 2016 at 19:06

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One approach would be to use a Convolutional Neural Network (CNN) since they are good at finding spatial patterns. You'll have to define a tensor for input (latitude, longitude, time, intensity).

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