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ORCIDEitaro Aiyoshi
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2020 – today
- 2021
[j10]Emiyu Ogawa
, Eitaro Aiyoshi, Tsunenori Arai:
A three-compartment non-linear model of myocardial cell conduction block during photosensitization. Medical Biol. Eng. Comput. 59(3): 703-710 (2021)
2010 – 2019
- 2015
- [j9]Yuji Koguma, Eitaro Aiyoshi:
A New Framework with a Stability Theory for Multipoint-Type and Stochastic Meta-Heuristic Optimization Algorithms. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 98-A(2): 700-709 (2015) - 2013
- [c10]Takashi Okamoto, Eitaro Aiyoshi:
Gamification of the Optimization Problem and Multi-point Type Optimization Methods. SMC 2013: 3516-3522 - 2011
- [j8]Eitaro Aiyoshi, Atsushi Maki, Takashi Okamoto:
The robustness of a Nash equilibrium simulation model: Game-theoretic approach using variable metric projection method. Math. Comput. Simul. 81(7): 1518-1526 (2011) - [c9]Kazuaki Masuda, Kenzo Kurihara, Eitaro Aiyoshi:
A novel method for solving min-max problems by using a modified particle swarm optimization. SMC 2011: 2113-2120 - 2010
- [c8]Kazuaki Masuda, Kenzo Kurihara, Eitaro Aiyoshi:
A penalty approach to handle inequality constraints in particle swarm optimization. SMC 2010: 2520-2525
2000 – 2009
- 2009
- [j7]Eitaro Aiyoshi, Atsushi Maki:
A Nash equilibrium solution in an oligopoly market: The search for Nash equilibrium solutions with replicator equations derived from the gradient dynamics of a simplex algorithm. Math. Comput. Simul. 79(9): 2724-2732 (2009) - 2008
- [j6]Takashi Okamoto, Eitaro Aiyoshi:
Global optimization using a synchronization of multiple search Points autonomously driven by a chaotic dynamic model. J. Glob. Optim. 41(2): 219-244 (2008) - 2007
- [c7]Fukiko Kawai, Hideyuki Ito, Chikashi Nakazawa, Tetsuro Matsui, Yoshikazu Fukuyama, Ryohei Suzuki, Eitaro Aiyoshi:
Automatic Tuning for Model Predictive Control: Can Particle Swarm Optimization find a better parameter? ISIC 2007: 646-651 - [c6]Ryohei Suzuki, Fukiko Kawai, Hideyuki Ito, Chikashi Nakazawa, Yoshikazu Fukuyama, Eitaro Aiyoshi:
Automatic Tuning of Model Predictive Control Using Particle Swarm Optimization. SIS 2007: 221-226 - 2004
- [c5]Yoko Kobayashi, Eitaro Aiyoshi:
Automatic core design using reinforcement learning. ACC 2004: 5784-5789 - [c4]Yoko Kobayashi, Eitaro Aiyoshi:
Optimization algorithm using multi-agents and reinforcement learning. IEEE Congress on Evolutionary Computation 2004: 63-68 - [c3]Kazuaki Masuda, Eitaro Aiyoshi:
Recurrent network expression and its property of replicator dynamics for optimization. SMC (4) 2004: 3488-3493 - 2003
- [c2]Yoko Kobayashi, Eitaro Aiyoshi:
Integrative two-state optimization for core design of BWR using genetic algorithms. CCA 2003: 109-114 - 2002
- [j5]Eitaro Aiyoshi, Ryota Horie, Atsushi Maki:
An application of the continuous time replicator dynamic to economics. Math. Comput. Simul. 59(1-3): 105-113 (2002)
1990 – 1999
- 1999
- [j4]Kuniharu Arai, Sanjoy Das, Edward L. Keller, Eitaro Aiyoshi:
A distributed model of the saccade system: simulations of temporally perturbed saccades using position and velocity feedback. Neural Networks 12(10): 1359-1375 (1999) - 1998
- [c1]Ryota Horie, Eitaro Aiyoshi:
Neural networks realization of searching models for Nash equilibrium points and their application to associative memories. SMC 1998: 1886-1891 - 1996
- [j3]Keiko Nagase, Eitaro Aiyoshi:
The hierarchical and social decision making procedure for bi-objective optimization problems by using the simple majority decision rule. J. Glob. Optim. 8(3): 307-322 (1996) - 1992
- [j2]Yo Ishizuka, Eitaro Aiyoshi:
Double penalty method for bilevel optimization problems. Ann. Oper. Res. 34: 73-88 (1992)
1980 – 1989
- 1982
- [j1]Kiyotaka Shimizu, Eitaro Aiyoshi:
A new solution to optimization-satisfaction problems by a penalty method. Autom. 18(1): 37-46 (1982)
Coauthor Index
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