Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Trading Data for Wind Power Forecasting: A Regression Market with Lasso
  Regularization   This paper proposes a regression market for wind agents to monetize data
traded among themselves for wind power forecasting. Existing literature on data
markets often treats data disclosure as a binary choice or modulates the data
quality based on the mismatch between the offer and bid prices. As a result,
the market disadvantages either the data sellers due to the overestimation of
their willingness to disclose data, or the data buyers due to the lack of
useful data being provided. Our proposed regression market determines the data
payment based on the least absolute shrinkage and selection operator (lasso),
which not only provides the data buyer with a means for selecting useful
features, but also enables each data seller to individualize the threshold for
data payment. Using both synthetic data and real-world wind data, the case
studies demonstrate a reduction in the overall losses for wind agents who buy
data, as well as additional financial benefits to those who sell data.

0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas