Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multivariate, Multistep Forecasting, Reconstruction and Feature
  Selection of Ocean Waves via Recurrent and Sequence-to-Sequence Networks   This article explores the concepts of ocean wave multivariate multistep
forecasting, reconstruction and feature selection. We introduce recurrent
neural network frameworks, integrated with Bayesian hyperparameter optimization
and Elastic Net methods. We consider both short- and long-term forecasts and
reconstruction, for significant wave height and output power of the ocean
waves. Sequence-to-sequence neural networks are being developed for the first
time to reconstruct the missing characteristics of ocean waves based on
information from nearby wave sensors. Our results indicate that the Adam and
AMSGrad optimization algorithms are the most robust ones to optimize the
sequence-to-sequence network. For the case of significant wave height
reconstruction, we compare the proposed methods with alternatives on a
well-studied dataset. We show the superiority of the proposed methods
considering several error metrics. We design a new case study based on
measurement stations along the east coast of the United States and investigate
the feature selection concept. Comparisons substantiate the benefit of
utilizing Elastic Net. Moreover, case study results indicate that when the
number of features is considerable, having deeper structures improves the
performance.

27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat