Hiroyuki Narihisa

Publication Activity (10 Years)

Years Active: 1991-2008
Publications (10 Years): 0

Publications

Hirotaka Inoue, Hiroyuki Narihisa
Efficient Incremental Learning with Self-Organizing Neural Grove. DMIN (2008)
Kengo Katayama, Hiroshi Yamashita, Hiroyuki Narihisa
Variable depth search and iterated local search for the node placement problem in multihop WDM lightwave networks. IEEE Congress on Evolutionary Computation (2007)
Hirotaka Inoue, Hiroyuki Narihisa
Efficient Incremental Learning Using Self-Organizing Neural Grove. ICONIP (1) (2007)
Kengo Katayama, Masashi Sadamatsu, Hiroyuki Narihisa
Iterated k-Opt Local Search for the Maximum Clique Problem. EvoCOP (2007)
Hiroyuki Narihisa, Keiko Kohmoto, Takahiro Taniguchi, Mayumi Ohta, Kengo Katayama
Evolutionary Programming With Only Using Exponential Mutation. IEEE Congress on Evolutionary Computation (2006)
Hiroyuki Narihisa, Takahiro Taniguchi, Mayumi Ohta, Kengo Katayama
Exponential Evolutionary Programming Without Self-Adaptive Strategy Parameter. IEEE Congress on Evolutionary Computation (2006)
Kengo Katayama, Akihiro Hamamoto, Hiroyuki Narihisa
An effective local search for the maximum clique problem. Inf. Process. Lett. 95 (5) (2005)
Hiroyuki Narihisa, Takahiro Taniguchi, Michiaki Thuda, Kengo Katayama
Efficiency of Parallel Exponential Evolutionary Programming. ICPP Workshops (2005)
Hirotaka Inoue, Hiroyuki Narihisa
Self-organizing neural grove: effective multiple classifier system with pruned self-generating neural trees. ISCAS (3) (2005)
Hirotaka Inoue, Hiroyuki Narihisa
Parallel performance of ensemble self-generating neural networks for chaotic time series prediction problems. Systems and Computers in Japan 36 (10) (2005)
Kengo Katayama, Takahiro Koshiishi, Hiroyuki Narihisa
Reinforcement learning agents with primary knowledge designed by analytic hierarchy process. SAC (2005)
Kengo Katayama, Akihiro Hamamoto, Hiroyuki Narihisa
Solving the maximum clique problem by k-opt local search. SAC (2004)
Hirotaka Inoue, Hiroyuki Narihisa
Self-organizing Neural Grove: Efficient Multiple Classifier System Using Pruned Self-generating Neural Trees. PPSN (2004)
Hirotaka Inoue, Hiroyuki Narihisa
Effective Pruning Method for a Multiple Classifier System Based on Self-Generating Neural Networks. ICANN (2003)
Hirotaka Inoue, Hiroyuki Narihisa
Improving Performance of a Multiple Classifier System Using Self-generating Neural Networks. Multiple Classifier Systems (2003)
Hirotaka Inoue, Hiroyuki Narihisa
Optimizing a Multiple Classifier System. PRICAI (2002)
Kengo Katayama, Hiroyuki Narihisa
Performance of simulated annealing-based heuristic for the unconstrained binary quadratic programming problem. Eur. J. Oper. Res. 134 (1) (2001)
Kengo Katayama, Hiroyuki Narihisa
On fundamental design of parthenogenetic algorithm for the binary quadratic programming problem. CEC (2001)
Hirotaka Inoue, Hiroyuki Narihisa
Parallel and Distributed Mining with Ensemble Self-Generating Neural Networks. ICPADS (2001)
Hirotaka Inoue, Yoshinobu Fukunaga, Hiroyuki Narihisa
Efficient Hybrid Neural Network for Chaotic Time Series Prediction. ICANN (2001)
Hirotaka Inoue, Hiroyuki Narihisa
Predicting Chaotic Time Series by Ensemble Self-Generating Neural Networks. IJCNN (2) (2000)
Hirotaka Inoue, Hiroyuki Narihisa
Improving Generalization Ability of Self-Generating Neural Networks Through Ensemble Averaging. PAKDD (2000)
Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa
Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm. GECCO (2000)
Kengo Katayama, Hiroyuki Narihisa
A New Iterated Local Search Algorithm Using Genetic Crossover for the Traveling Salesman Problem. SAC (1999)
Kengo Katayama, Hisayuki Hirabayashi, Hiroyuki Narihisa
Performance analysis for crossover operators of genetic algorithm. Systems and Computers in Japan 30 (2) (1999)
Hiroshi Ohtera, Shigeru Yamada, Hiroyuki Narihisa
Software reliability growth model for testing-domain. Systems and Computers in Japan 22 (2) (1991)