Publication List
Refereed journal papers
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[New] M. U. Kobayashi, K. Nakai, Y. Saiki and N. Tsutsumi, On the model attractor in a high-dimensional neural network dynamics of reservoir computing, Chaos 36(5), 053115, 2026 (published online May 5). https://doi.org/10.1063/5.0315384 https://arxiv.org/abs/2509.12733
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N. Tsutsumi and K. Nakai and Y. Saiki, Data-driven ODE modeling of the high-frequency complex dynamics via a low-frequency dynamics model, Phys.Rev.E 111 (1), 014212:1-6, 2025(published January 7). https://doi.org/10.1103/PhysRevE.111.014212 https://arxiv.org/abs/2409.00668
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N. Tsutsumi and K. Nakai and Y. Saiki, Constructing low-dimensional ordinary differential equations from chaotic time series of high- or infinite-dimensional systems using radial-function-based regression, Physical Review E 108 (5), 054220:1-13, 2023 (published November 22). https://doi.org/10.1103/PhysRevE.108.054220 https://arxiv.org/abs/2308.12382
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N. Tsutsumi and K. Nakai and Y. Saiki, Constructing differential equations usi
ng only a scalar time-series about continuous time chaotic dynamics, Chaos 32(9), 091101, 2022 (published online September 12).https://doi.org/10.1063/5.0100166 https://arxiv.org/abs/2209.06000
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M. U. Kobayashi, K. Nakai, Y. Saiki and N. Tsutsumi, Dynamical system analysis of a data-driven model constructed by reservoir computing, Physical Review E 104 (4), 044215:1-7, 2021 (published October 28). https://doi.org/10.1103/PhysRevE.104.044215 https://arxiv.org/abs/2102.13475
Preprint
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Natsuki Tsutsumi, Kengo Nakai and Yoshitaka Saiki, Geometric structure of ideal data-driven dynamical model using RfR method, arXiv. https://arxiv.org/abs/2604.10550
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N.Tsutsumi, データ駆動型微分方程式の導出, 北海道大学数学講究録 184, 239-246,2023. MCYR19 Technical Reports.pdf https://doi.org/10.14943/106347
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N.Tsutsumi, 小売カンバンモデルを用いた在庫最適化理論, 2022. (学部 卒業論文)
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N.Tsutsumi, データ駆動時系列モデリングによる微分方程式の導出, 北海道大学数学講究録 182, 647-656, 2022. tech182.pdf https://doi.org/10.14943/101654
Oral presentation / Poster session
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Geometric structure of data-driven dynamical model using RfR method, MLDS5&DEDS2026, 2026.
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Theoretical analysis of a linearized optimization problem for convection control in finite time, Dynamics Days US 2026, 2026.[poster]
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線形安定なモデル対流の有限時間のパターン制御, 応用数学合同研究集会, 2025.
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Optimal perturbation of coupled map lattice, Tateyama Dynamics Workshop 2025, 2025.
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Convection Control using a Coupled Map Lattice Model, Mini-Workshop on Mathematical Weather Control and Prediction, 2025.
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RfR法によるデータ駆動力学系モデルの幾何学的構造解析, 応用数理学会年会, 2025.
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Ideal data-driven model using RfR method and its dynamical system analysis, Winter Annual Conference on Dynamical Systems 2024, 2025.
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データ駆動低次元力学系モデリング手法を用いた全リアプノフ指数の推定, Dynamics Days Sapporo 2024, 2024.
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Construction of data-driven differential equations describing a fluid flow, Tateyama Dynamics Workshop 2024, 2024.
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Data-driven ordinary differential equations of macroscopic dynamics of a fluid flow, Dynamics Days 2023, 2023.
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Constructing data-driven ODEs of a chaotic fluid flow, KiPAS Dynamics Days 2023, 2023.[poster]
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Constructing data-driven ODEs of a chaotic fluid flow, International Congress on Industrial and Applied Mathematics 2023 Tokyo, 2023.[poster]
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Construct ODEs describing the macroscopic variables of the fluid system, International Workshop on Ergodic Theory, Dynamical Systems, and Climate Sciences, 2023.[poster]
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データ駆動型微分方程式の導出, 第19回数学総合若手研究集会, 2023.
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流体マクロ時系列のデータ駆動時系列モデリング, 応用数学合同研究集会, 2022.
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データ駆動時系列モデリングによる微分方程式の導出, 第18回数学総合若手研究集会, 2022.
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費用最小化を目的とした単純な適応型グループテストにおける最適グループ人数に関する一 考察, 異分野・異業種研究交流会2020, 2020.[poster]
Prize
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一般社団法人ヤマトグループ総合研究所 第3回懸賞論文「2030年の物流 －ニューノーマルに対応した物流－」特別賞
https://www.yamato-hd.co.jp/news/2022/newsrelease_20220411_2.html