Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimating State of Charge for xEV batteries using 1D Convolutional
  Neural Networks and Transfer Learning   In this paper we propose a one-dimensional convolutional neural network
(CNN)-based state of charge estimation algorithm for electric vehicles. The CNN
is trained using two publicly available battery datasets. The influence of
different types of noises on the estimation capabilities of the CNN model has
been studied. Moreover, a transfer learning mechanism is proposed in order to
make the developed algorithm generalize better and estimate with an acceptable
accuracy when a battery with different chemical characteristics than the one
used for training the model, is used. It has been observed that using transfer
learning, the model can learn sufficiently well with significantly less amount
of battery data. The proposed method fares well in terms of estimation
accuracy, learning speed and generalization capability.

29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th