Eitaro Aiyoshi - researchr alias

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Viewing Publication 1 - 19 from 19

2021

A three-compartment non-linear model of myocardial cell conduction block during photosensitizationEmiyu Ogawa, Eitaro Aiyoshi, Tsunenori Arai. mbec, 59(3):703-710, 2021. [doi]

2015

A New Framework with a Stability Theory for Multipoint-Type and Stochastic Meta-Heuristic Optimization AlgorithmsYuji Koguma, Eitaro Aiyoshi. ieicet, 98-A(2):700-709, 2015. [doi]

2013

Gamification of the Optimization Problem and Multi-point Type Optimization MethodsTakashi Okamoto, Eitaro Aiyoshi. SMC 2013: 3516-3522 [doi]

2011

The robustness of a Nash equilibrium simulation model: Game-theoretic approach using variable metric projection methodEitaro Aiyoshi, Atsushi Maki, Takashi Okamoto. mcs, 81(7):1518-1526, 2011. [doi]

A novel method for solving min-max problems by using a modified particle swarm optimizationKazuaki Masuda, Kenzo Kurihara, Eitaro Aiyoshi. SMC 2011: 2113-2120 [doi]

2010

A penalty approach to handle inequality constraints in particle swarm optimizationKazuaki Masuda, Kenzo Kurihara, Eitaro Aiyoshi. SMC 2010: 2520-2525 [doi]

2009

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 algorithmEitaro Aiyoshi, Atsushi Maki. mcs, 79(9):2724-2732, 2009. [doi]

2008

Global optimization using a synchronization of multiple search Points autonomously driven by a chaotic dynamic modelTakashi Okamoto, Eitaro Aiyoshi. jgo, 41(2):219-244, 2008. [doi]

2007

Automatic Tuning for Model Predictive Control: Can Particle Swarm Optimization find a better parameter?Fukiko Kawai, Hideyuki Ito, Chikashi Nakazawa, Tetsuro Matsui, Yoshikazu Fukuyama, Ryohei Suzuki, Eitaro Aiyoshi. IEEEisic 2007: 646-651 [doi]

Automatic Tuning of Model Predictive Control Using Particle Swarm OptimizationRyohei Suzuki, Fukiko Kawai, Hideyuki Ito, Chikashi Nakazawa, Yoshikazu Fukuyama, Eitaro Aiyoshi. kit 2007: 221-226 [doi]

2004

Optimization algorithm using multi-agents and reinforcement learningYoko Kobayashi, Eitaro Aiyoshi. cec 2004: 63-68 [doi]

Automatic core design using reinforcement learningYoko Kobayashi, Eitaro Aiyoshi. amcc 2004: 5784-5789 [doi]

Recurrent network expression and its property of replicator dynamics for optimizationKazuaki Masuda, Eitaro Aiyoshi. SMC 2004: 3488-3493 [doi]

2002

An application of the continuous time replicator dynamic to economicsEitaro Aiyoshi, Ryota Horie, Atsushi Maki. mcs, 59(1-3):105-113, 2002. [doi]

1999

A distributed model of the saccade system: simulations of temporally perturbed saccades using position and velocity feedbackKuniharu Arai, Sanjoy Das, Edward L. Keller, Eitaro Aiyoshi. NN, 12(10):1359-1375, 1999. [doi]

1998

Neural networks realization of searching models for Nash equilibrium points and their application to associative memoriesRyota Horie, Eitaro Aiyoshi. SMC 1998: 1886-1891 [doi]

1996

The hierarchical and social decision making procedure for bi-objective optimization problems by using the simple majority decision ruleKeiko Nagase, Eitaro Aiyoshi. jgo, 8(3):307-322, 1996. [doi]

1992

Double penalty method for bilevel optimization problemsYo Ishizuka, Eitaro Aiyoshi. anor, 34:73-88, 1992. [doi]

1982

A new solution to optimization-satisfaction problems by a penalty methodKiyotaka Shimizu, Eitaro Aiyoshi. automatica, 18(1):37-46, 1982. [doi]

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