Researchers

ISHIMIZU Takashi

ISHIMIZU Takashi
Lecturer
Faculty Department of Informatics
Researchmap https://researchmap.jp/TakashiIshimizu

Research Activities

Research Areas

  • Informatics, Information theory

Published Papers

  1. Concurrent differential evolution for uncertain optimization problems
    田川 聖治; 石水 隆
    The Fifth International Conference on Advanced Engineering Computing and Applications in Sciences  , 48-53, Nov. 2011 
  2. Alternative implementation techniques of parallelized Differential Evolution for multi-core processors
    Kiyaharu Tagawa; Takashi Ishimizu
    Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011  1  , 1-4, 2011  , Refereed
  3. Experimental study of a structured differential evolution with mixed strategies
    Takashi Ishimizu; Kiyoharu Tagawa
    Journal of Advanced Computational Intelligence and Intelligent Informatics  15  (9)  , 1310-1319, 2011  , Refereed

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Conference Activities & Talks

  1. 並列差分進化計算の比較研究 , 石水 隆; 田川 聖治 , 情報処理学会 数理モデルと問題解決研究 , Mar. 2011
  2. Experiment Study of A Structured Differential Evolution with Mixed Strategies , 石水 隆; 田川 聖治 , World Congress on Nature and Biologocally Inspired Computing , Dec. 2010
  3. An implementation of differential evolution for multi-core processors , 田川 聖治; 石水 隆 , 計測自動制御学会中部支部 , Oct. 2010

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MISC

  1. A Comparative Study of Parallel Differential Evolution , 石水 隆; 田川 聖治 , 研究報告数理モデル化と問題解決（MPS） , 2011 , 23 , 1 , 2 , 28, Feb. 2011
    Summary:本稿では差分進化計算 (DE) をプロセッサネットワーク上で並列化した並列差分進化計算 (PDE) を提案する．PDE ではプロセッサごとに異なる戦略を用いることにより，最適化問題に対し効率的，かつ高確率で解を求めることができる．In this paper, a Parallel Differential Evolution (PDE) that is a parallel implement of Differential Evolution (DE) on processor network, is proposed. The proposed PDE uses different strategies in respective processors, the optimal solution are found more efficiently in high probability.
  2. Parallel algorithms for the all nearest neighbors of binary image on the BSP model , T Ishimizu; A Fujiwara; M Inoue; T Masuzawa; H Fujiwara , IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS , E83D , 2 , 151 , 158 , Feb. 2000
    Summary:In this paper, we present two parallel algorithms for computing the all nearest neighbors of an n x n binary image on the Bulk-Synchronous Parallel (BSP) model. The BSP model is an asynchronous parallel computing model, where its communication features are abstracted by two parameters L and g: L denotes synchronization periodicity and g denotes a reciprocal of communication bandwidth. We propose two parallel algorithms for the ail nearest neighbor problems based on two distance metrics. The first algorithm is for L-p distance, and the second algorithm is for weighted distance. Both two algorithms run in O(n(2)/p + L) computation time and in O(g n/root p + L) communication time using p (1 less than or equal to p less than or equal to n) processors and in O(n(2)/p + (d + L) log p/n/log (d + 1)) computation time and in O(g n/root p + (gd + L) log p/n/log (d+1)) communication time using p (n < p less than or equal to n(2)) processors on the BSP model, for any integer d (1 less than or equal to d less than or equal to p/n).