Home
Author Guide
Editor Guide
Reviewer Guide
Published Issues
Special Issue
Introduction
Special Issues List
Sections and Topics
Sections
Topics
journal menu
Aims and Scope
Editorial Board
Indexing Service
Article Processing Charge
Open Access
Copyright and Licensing
Preservation and Repository Policy
Publication Ethics
Editorial Process
Contact Us
General Information
ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
ESCI (Web of Science)
,
Scopus
,
CNKI
,
etc
.
Acceptance Rate:
19%
APC:
500 USD
Average Days to Accept:
135 days
Journal Metrics:
Impact Factor 2022: 1.0
3.1
2022
CiteScore
49th percentile
Powered by
Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
What's New
2024-03-28
Vol. 15, No. 3 has been published online!
2024-02-26
The papers published in Vol. 15, Nos. 1&2 have been registered with Crossref.
2024-02-26
Vol. 15, No. 2 has been published online!
Home
>
Published Issues
>
2020
>
Volume 11, No. 3, August 2020
>
Prediction of Robot Technology Using Multi-phase Model
Juhyun Lee
1
, Junseok Lee
2
, Jiho Kang
1
, Sangsung Park
3
, and Dongsik Jang
1
1. Department of Industrial Management Engineering, Korea University, Republic of Korea
2. MICube Solution, Republic of Korea
3. Department of Big Data Statistics, CheongJu University, Republic of Korea
Abstract
—Technology changes with the times. It is difficult to predict, as technology develops under the influence of several factors. We analyze the technology by carrying out the patent from a time series perspective. The study consists of two phases. In the first phase, time series models detect the trend, cycle, and seasonality of the technology. Next phase performs to predict the importance of term. In order to confirm the practical applicability of the proposed method, 2,268 industrial robot patents were collected and tested. As a result, it was found that technologies beyond the dual control based on carbon materials among industrial robots will continue to develop.
Index Terms
—robot, patent analysis, time series, predictive modeling
Cite: Juhyun Lee, Junseok Lee, Jiho Kang, Sangsung Park, and Dongsik Jang, "Prediction of Robot Technology Using Multi-phase Model," Journal of Advances in Information Technology, Vol. 11, No. 3, pp. 181-185, August 2020. doi: 10.12720/jait.11.3.181-185
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
11-H0032_Korea
PREVIOUS PAPER
Wearable Technology in Healthcare
NEXT PAPER
Last page