Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Power Data Classification: A Hybrid of a Novel Local Time Warping and
  LSTM   In this paper, for the purpose of data centre energy consumption monitoring
and analysis, we propose to detect the running programs in a server by
classifying the observed power consumption series. Time series classification
problem has been extensively studied with various distance measurements
developed; also recently the deep learning based sequence models have been
proved to be promising. In this paper, we propose a novel distance measurement
and build a time series classification algorithm hybridizing nearest neighbour
and long short term memory (LSTM) neural network. More specifically, first we
propose a new distance measurement termed as Local Time Warping (LTW), which
utilizes a user-specified set for local warping, and is designed to be
non-commutative and non-dynamic programming. Second we hybridize the 1NN-LTW
and LSTM together. In particular, we combine the prediction probability vector
of 1NN-LTW and LSTM to determine the label of the test cases. Finally, using
the power consumption data from a real data center, we show that the proposed
LTW can improve the classification accuracy of DTW from about 84% to 90%. Our
experimental results prove that the proposed LTW is competitive on our data set
compared with existed DTW variants and its non-commutative feature is indeed
beneficial. We also test a linear version of LTW and it can significantly
outperform existed linear runtime lower bound methods like LB_Keogh.
Furthermore, with the hybrid algorithm, for the power series classification
task we achieve an accuracy up to about 93%. Our research can inspire more
studies on time series distance measurement and the hybrid of the deep learning
models with other traditional models.

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The categories of this paper are: atom-ph
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
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The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph