藤野 和志

学会誌論文

1. Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato, Multilayered Cortical Learning Algorithm for Forecasting Time-Series Data with Probabilistically Changing Trends, Journal of Signal Processing, Vo.l 27, Issue 4, p. 69-73, 2023.
2. Kazushi Fujino, Takeru Aoki, Keiki Takadama, and Hiroyuki Sato, “Adaptive Action-prediction Cortical Learning Algorithm under Uncertain Environments,” International Journal of Hybrid Intelligent Systems, 2023. (Accepted)

国際会議

1. Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato, “Cortical Learning Based Action-decision Under Uncertain Environment,” The 3rd ASEAN-UEC Workshop on Informatics and Engineering for SDGs, 2pages, 2021.
2. Kazushi Fujino, Takeru Aoki, Keiki Takadama and Hiroyuki Sato, “Adaptive Synapse Adjustment for Multivariate Cortical Learning Algorithm,” 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022), 2022.
3. Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato, “Adaptive Synapse Adjustment and Decoding in Action-prediction Cortical Learning Algorithm,” in Proc. of the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2022), 2022.
4. Kazushi Fujino, Takeru Aoki, Keiki Takadama, Hiroyuki Sato, “Multi-layer Cortical Learning Algorithm for Trend Changing Time-series Forecast,” 2023 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP2023), pp. 281–284, 2023.
5. Kazuma Niwa, Takeru Aoki, Kazushi Fujino, Keiki Takadama, and Hiroyuki Sato, “A Preliminary Study on Spatially Distributed Data Forecast Using Cortical Learning Algorithm,” The 5th ASEAN-UEC Workshop on Informatics and Engineering, 2pages, 2023.
6. Kazushi Fujino, Keiki Takadama, Hiroyuki Sato, “Multi-Layer Cortical Learning Algorithm for Forecasting Time-Series Data with Smoothly Changing Variation Patterns,” 2024 IEEE World Congress on Computational Intelligence (IEEE WCCI 2024), 2024.

国内学会

1. 藤野和志，青木健，高玉圭樹，佐藤寛之, “時系列予測に基づく行動決定のための大脳新皮質学習に関する基礎検討,” 第17回コンピューテーショナル・インテリジェンス研究会，システム・情報部門，計測自動制御学会，pp. 63–67, 2021.
2. 藤野和志，青木健，高玉圭樹，佐藤寛之, “多変量大脳新皮質学習アルゴリズムのための適応的シナプス調整,” 第20回コンピューテーショナル・インテリジェンス研究会, 計測自動制御学会，pp. 53–60，2022．
3. 藤野 和志，青木 健，高玉 圭樹，佐藤 寛之，“大脳新皮質学習における適応的なシナプス調整と予測値デコードの効果”, システム・情報部門学術講演会2022 (SSI2022)，計測自動制御学会，2022.

受賞

1. 2020年度目黒会賞，2021/3/25.
2. Student Paper Award, 2023 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, Mar. 4, 2023.
3. 2022年度学生表彰，電気通信大学，2023/3/25.

運営

• 情報処理学会 第131回数理モデル化と問題解決(MPS)研究会運営スタッフ