FURUZUKI, Takayuki

J-GLOBAL         Last updated: Sep 7, 2019 at 03:54
FURUZUKI, Takayuki
Alternative names
HU, Jinglu
Waseda University
Faculty of Science and Engineering Graduate School of Information, Production, and Systems
Job title
PhD(Kyushu Institute of Technology)
Research funding number

Research Areas



Sep 1979
Jul 1983
Electronics Engineering, Electrical & Electronic Systems Engineering, Sun Yat-Sen University
Sep 1986
Jul 1986
Electronics Engineering, Graduate School, Division of Information Engineering, Sun Yat-Sen University
Apr 1994
Mar 1997
Information Science, Graduate School, Division of Information Engineering, Kyushu Institute of Technology

Awards & Honors

Nov 2008
ISCIIA2008 Excellent Paper Award

Published Papers

An Autoencoder Based Piecewise Linear Model for Nonlinear Classification using Quasi-Linear Support Vector Machines
W. Li, P. Liang and J. Hu
IEEJ Trans. on Electrical and Electronic Engineering C   14(8)    Aug 2019   [Refereed]
B. Zhou, W.Li and J.Hu
IEEJ Trans. on Electrical and Electronic Engineering C   14(3) 441-448   Mar 2019   [Refereed]
P. Liang, W.Li, H.Tian and J.Hu
IEEJ Trans. on Electrical and Electronic Engineering C   14(3) 449-456   Mar 2019   [Refereed]
P. Liang, F. Zheng, W.Li and J.Hu
IEEJ Trans. on Electrical and Electronic Engineering C   14(2) 288-296   Feb 2019   [Refereed]
P. Liang, W. Li and J. Hu
IEEJ Trans. on Electrical and Electronic Engineering C   13(10) 1483-1491   Oct 2018   [Refereed]

Books etc

「進化技術ハンドブック」、第21章 21.1 自己組織化機能局在型ニューラルネットワーク、21.4 非線形多項式モデルの同定
古月 敬之 (Part:Contributor)
近代科学社、東京   Nov 2011   ISBN:978-4-7649-0418-7
Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA
Benhui Chen and Jinglu Hu (Part:Contributor)
Exploitation of Linkage Learning in Evolutionary Algorithms, Springer-Verlag, Berlin, Germany   May 2010   ISBN:978-3-642-12833-2
「ニューラルネットワーク計算知能」、第2章 線形特性を有するニューラルネットワーク
古月 敬之 (Part:Contributor)
森北出版株式会社, 東京   Sep 2006   ISBN:4-627-82991-4
A Method for Applying Neural Networks to Control of Nonlinear Systems
J.Hu and K.Hirasawa (Part:Contributor)
Neural Information Processing Research and Development, Springer, Berlin, Germany   May 2004   ISBN:3-540-21123-3
Statistical Methods for Robust Change Detection in Dynamical Systems with Model Uncertainty
K. Kumamaru, J. Hu, K.Inoue and T. Soderstrom (Part:Contributor)
Statistical Methods in Control and Signal Processing, Mercel Dekker Inc., New York, USA   Aug 1997   ISBN:0824799488

Research Grants & Projects

Deep Quasi-Linear SVM Based on Deep Neural Network and Its Applications
Project Year: Apr 2017 - Mar 2020
Study on Quasi-Linear Support Vector Machine and Its Applications
Project Year: Apr 2013 - Mar 2017
In this research, a quasi-linear support vector machine (SVM) is proposed. The quasi-linear SVM, on one hand, can be seen as a nonlinear SVR model with easy-to-use structure; on the other hand, it is a nonlinear SVM with data-dependent kernel, whi...
Project Year: 2006 - 2009
Function localization and layer structure are two basic features of complex systems. In this research, we developed two hierarchical function localized brain-like systems : one is Self-organizing function localized learning system with supervised ...
Project Year: 2005 - 2008
Genetic Algorithm (GA), a method which imitates nature and living things, was proposed as a model which explains the adaptive process of the system of nature. In addition, Genetic Programming (GP) was proposed to deal with knowledge expression, pr...
Project Year: 2002 - 2005
Intelligent system consisting of multi-individuals interacting between each other have been developed and the learning and evolution of the system have been studied. It is shown that the proposed system has better performance than conventional met...