<p>Are you really sure that a CNN is what you want? It might not be the best choice for sequential data. If you want to learn more about alternative ways to deal with sequential data (like time series), I recommend reading the paper "<a href="https://arxiv.org/abs/1602.01711" rel="nofollow noreferrer">The Great Time Series Classification Bake Off</a>".</p>

<p>I especially recommend looking into <a href="https://en.wikipedia.org/wiki/Dynamic_time_warping" rel="nofollow noreferrer">Dynamic time warping</a> first. It might not be a bleeding edge deep learning algorithm but turns out to be very hard to beat when it comes to classifying sequential data.</p>
How to preprocessing sequential data for 2D-CNN
<p>Is there any way to transform sequential data to 2-dimensional data in order to use it for a common CNN?</p>

<p>My dataset Looks like: 14,40,84,120,38,29,395,58,153,...</p>

<p>But I need a 2-dimensional representation for that. Is there any established algorithm for that purpose?</p>