Prediction of robot technology using multi-phase model

Juhyun Lee; Junseok Lee; Jiho Kang; Sangsung Park; Dongsik Jang

doi:10.12720/jait.11.3.181-185

Prediction of robot technology using multi-phase model

Juhyun Lee, Junseok Lee, Jiho Kang, Sangsung Park, Dongsik Jang

School of Industrial Management Engineering

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

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.

Original language	English
Pages (from-to)	181-185
Number of pages	5
Journal	Journal of Advances in Information Technology
Volume	11
Issue number	3
DOIs	https://doi.org/10.12720/jait.11.3.181-185
Publication status	Published - 2020 Aug

Keywords

Patent analysis
Predictive modeling
Robot
Time series

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Artificial Intelligence
Software
Computer Networks and Communications

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10.12720/jait.11.3.181-185

Cite this

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title = "Prediction of robot technology using multi-phase model",

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.",

keywords = "Patent analysis, Predictive modeling, Robot, Time series",

author = "Juhyun Lee and Junseok Lee and Jiho Kang and Sangsung Park and Dongsik Jang",

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doi = "10.12720/jait.11.3.181-185",

language = "English",

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T1 - Prediction of robot technology using multi-phase model

AU - Lee, Juhyun

AU - Lee, Junseok

AU - Kang, Jiho

AU - Park, Sangsung

AU - Jang, Dongsik

N1 - Funding Information: This research was supported by the MOTIE (Ministry of Trade, Industry, and Energy) in Korea, under the Fostering Global Talents for Innovative Growth Program (P0008749) supervised by the Korea Institute for Advancement of Technology (KIAT). Publisher Copyright: © 2020 J. Adv. Inf. Technol.

PY - 2020/8

Y1 - 2020/8

N2 - 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.

AB - 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.

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Prediction of robot technology using multi-phase model

Abstract

Keywords

ASJC Scopus subject areas

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