Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analysing and visualising bike sharing demand with outliers   Bike-sharing is a popular component of sustainable urban mobility. It
requires anticipatory planning, e.g. of terminal locations and inventory, to
balance expected demand and capacity. However, external factors such as extreme
weather or glitches in public transport, can cause demand to deviate from
baseline levels. Identifying such outliers keeps historic data reliable and
improves forecasts. In this paper we show how outliers can be identified by
clustering terminals and applying a functional depth analysis. We apply our
analysis techniques to the Washington D.C. Capital Bikeshare data set as the
running example throughout the paper, but our methodology is general by design.
Furthermore, we offer an array of meaningful visualisations to communicate
findings and highlight patterns in demand. Last but not least, we formulate
managerial recommendations on how to use both the demand forecast and the
identified outliers in the bike-sharing planning process.

14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
1
The categories of this paper are: cs
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol