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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CCS, NLP | 2023-06-09 11:10 |
Tokyo | Tokyo City Univ. | A study on learning Koopman operators from synchrophasor data on distribution voltage amplitudes Tadahiro Yano, Yoshihiko Susuki (Kyoto Univ.)  NLP2023-21 CCS2023-9 |
In recent years, the so-called micro-Phasor Measurement Unit ($mu$PMU) has become a promising new option for managing AC... [more] | NLP2023-21 CCS2023-9 pp.35-38 |
| NLP, MSS | 2023-03-15 10:40 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Spectral analysis of synchropahsor data in a campus distribution grid: Comparison of numerical methods Munetaka Noguchi (Osaka Prefecture Univ.), Yoshihiko Susuki (Kyoto Univ.), Atsushi Ishigame (Osaka Metropolitan Univ.) MSS2022-64 NLP2022-109 |
Recently, the so-called micro-Phasor Measurement Unit (μPMU) with high-resolution capability has been expected as a new ... [more] | MSS2022-64 NLP2022-109 pp.11-16 |
| NLP, MSS | 2023-03-16 11:40 |
Nagasaki | (Primary: On-site, Secondary: Online) |
A Study on Properties of Koopman Eigenfunctions for a Planar Singularly-Perturbed Dynamical System Natsuki Katayama, Yoshihiko Susuki (Kyoto Univ.) MSS2022-85 NLP2022-130 |
The Koopman operator is a composition operator for nonlinear dynamical systems. The eigenfunctions of the Koopman operat... [more] | MSS2022-85 NLP2022-130 pp.114-119 |
| NLP | 2022-11-25 15:40 |
Shiga | (Primary: On-site, Secondary: Online) |
A study on Participation factor for nonlinear dynamical systems based on Koopman mode decomposition Kenji Takamichi (Osaka Prefecture Univ.), Yoshihiko Susuki (Kyoto Univ.), Marcos Netto (NREL), Atsushi Ishigame (Osaka Prefecture Univ.) NLP2022-79 |
The so-called participation factor analysis has been used to evaluate the relative contribution between state vari- able... [more] | NLP2022-79 pp.103-108 |
| NLP | 2022-08-02 11:15 |
Online | Online | [Invited Talk]
Koopman-operator approach to dimensionality reduction of dynamical systems and applications to nonlinear rhythms Hiroya Nakao (Tokyo Tech.) NLP2022-31 |
A method of dimensionality reduction for nonlinear dynamical systems via the Koopman operator theory and its application... [more] | NLP2022-31 pp.24-26 |
| NLP, CCS | 2021-06-11 10:50 |
Online | Online | A Study on Prediction of Synchrophasor Time-Series Data of In-Campus Distribution Voltage Using Gaussian Process Regression Munetaka Noguchi (Osaka Pref Univ.), Yoshihiko Susuki (Osaka Pref Univ./JST), Atsushi Ishigame (Osaka Pref Univ.) NLP2021-3 CCS2021-3 |
Due to recent penetration of distributed energy resources, dynamics of power distribution systems have been complicated ... [more] | NLP2021-3 CCS2021-3 pp.10-13 |
| IBISML | 2020-10-21 16:15 |
Online | Online | IBISML2020-25 |
Analysis and prediction of dynamic processes using data are fundamental in a variety of scientific and industrial fields... [more] | IBISML2020-25 pp.43-44 |
| CCS | 2019-03-27 10:30 |
Tokyo | NICT, Koganei, Tokyo | [Invited Talk]
Analysis and Control of Nonlinear Dynamical Systems via the Koopman Operator Yoshihiko Susuki (Osaka Pref. Univ.) CCS2018-56 |
The Koopman operator is a composition operator defined for a large class of nonlinear dynamical systems. Even if a ta... [more] |
CCS2018-56 p.55 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
On comparison of dynamical systems via Perron-Frobenius operators on reproducing kernel Hilbert spaces Isao Ishikawa (RIKEN/Keio Univ.), Keisuke Fujii (RIKEN), Masahiro Ikeda (RIKEN/Keio Univ.), Yuka Hashimoto (Keio Univ.), Yoshinobu Kawahara (Osaka Univ/RIKEN.) IBISML2018-67 |
The development of a metric for structural data is a long-term problem in pattern recognition and machine learning. In t... [more] | IBISML2018-67 pp.175-182 |
| CCS, NLP | 2016-06-13 11:30 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Optimal parameter selection for kernel dynamic mode decomposition Wataru Kurebayashi (Aomori Univ.), Sho Shirasaka, Hiroya Nakao (Tokyo Tech.) NLP2016-21 CCS2016-4 |
A novel mode decomposition method based on the dynamical systems theory, called the dynamic mode decomposition (DMD), ha... [more] | NLP2016-21 CCS2016-4 pp.13-14 |
| NLP | 2013-12-06 16:05 |
Overseas | City University of Hong Kong | Data-Based Stability Assessment of Power Grids without Models
-- Application of Koopman Operator Methods -- Yoshihiko Susuki (Kyoto Univ./JST), Igor Mezic (UCSB) NLP2013-118 |
We present a data-based approach to stability assessment of power systems without models. This approach is enabled by K... [more] | NLP2013-118 pp.29-34 |
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