T. Okamoto

发表

Constrained optimization using a multipoint type chaotic Lagrangian method with a coupling structure

H. Hirata, T. Okamoto, 2013 .

Visualization of Pareto Optimal Solution Sets Using the Growing Hierarchical Self-Organizing Maps

S. Koakutsu, T. Okamoto, Naoto Suzuki, 2017 .

The Improved Draining Method and Its Application to Proper Benchmark Problems

E. Aiyoshi, T. Okamoto, 2006, 2006 SICE-ICASE International Joint Conference.

Analysis and Improvements of the Pareto Optimal Solution Visualization Method Using the Self-Organizing Maps

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2015 .

Global optimization with the PSO coupling‐type discrete gradient chaos model

E. Aiyoshi, T. Okamoto, 2008 .

Global optimization using a multipoint type quasi-chaotic optimization method

Takashi Okamoto, Hironori Hirata, H. Hirata, 2013, Appl. Soft Comput..

Mixed integer optimization using the quasi-chaotic optimization with the discrete simultaneous perturbation stochastic approximation

H. Hirata, T. Okamoto, 2011, SICE Annual Conference 2011.

Constrained optimization using the lagrangian method and the improved discrete gradient chaos model

Takashi Okamoto, Hironori Hirata, H. Hirata, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Visualization of Pareto optimal solutions using MIGSOM

Takashi Okamoto, Seiichi Koakutsu, Naoto Suzuki, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

The global optimization with the PSO coupling type discrete gradient chaos model

Takashi Okamoto, Eitaro Aiyoshi, E. Aiyoshi, 2006 .

A Learning Method for Block-Based Neural Networks Using Particle Swarm Optimization

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2009 .

Constrained optimization using the chaotic sequential quadratic approximation type Lagrange quasi-Newton method

Takashi Okamoto, T. Okamoto, 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Chaotic Optimization Method without Initial Sampling Parameter Tuning - Empirical Comparisons of Two Approaches in Various Problems

Takashi Okamoto, Hironori Hirata, H. Hirata, 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

Constrained optimization using the chaotic Lagrange quasi-Newton method - A basic study of its search trajectory and its search capability

Hironori Hirata, H. Hirata, T. Okamoto, 2013, The SICE Annual Conference 2013.

Global optimization using a multi-point type quasi-chaotic optimization method with the simultaneous perturbation gradient approximation

Takashi Okamoto, Hironori Hirata, H. Hirata, 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

Global optimization using the draining method and the simultaneous perturbation gradient approximation

H. Hirata, T. Okamoto, 2010, Proceedings of SICE Annual Conference 2010.

Global optimization using a synchronization of multiple search Points autonomously driven by a chaotic dynamic model

Takashi Okamoto, Eitaro Aiyoshi, E. Aiyoshi, 2008, J. Glob. Optim..

TheImproved Draining Methodand ItsApplication toProper Benchmark Problems

Takashi Okamoto, T. Okamoto, 2006 .

A Chaotic Optimization Method Using a Bifurcation Tuning by an Objective Function Transformation : A Proposal of Global Optimization Method “Draining Method”

Takashi Okamoto, Eitaro Aiyoshi, Yuki Watanabe, 2006 .

A Collaborative Learning Automata Team Model for Modeling Multi-Agent Systems

Takashi Okamoto, Seiichi Koakutsu, Cen Wang, 2018 .

A Chaotic Optimization Method without Initial Sampling Parameter Tuning

Takashi Okamoto, Hironori Hirata, H. Hirata, 2012 .

A Learning Method for Block-Based Neural Networks with Structure Search Based on the Least Number of Routes

Takashi Okamoto, Seiichi Koakutsu, Naoto Norimatsu, 2017 .

Block-Based Neural Networks with Pulsed Neuron Model (Japanese Title: ??????????????????????????????

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2010 .

Profit Sharing Using a Dynamic Reinforcement Function Considering Expectation Value of Reinforcement

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2009 .

Fast Back Propagation Learning Using Optimization of Learning Rate for Pulsed Neural Networks

Kenji Yamamoto, Takashi Okamoto, Hironori Hirata, 2008 .

Global Optimization Using a Multi-point Type Quasi-chaotic Optimization Method without Initial Sampling Parameter Tuning

Takashi Okamoto, Hironori Hirata, H. Hirata, 2010, Soft Computing Models in Industrial and Environmental Applications.

Multi-Objective Optimization Using Coupled Discrete Gradient Model

Hironori Hirata, H. Hirata, T. Okamoto, 2010 .

Optimal Design of Buffer Material in the Geological Disposal of Radioactive Wastes Using the Satisficing Trade‐off Method and a Self‐Organizing Map

Takashi Okamoto, Eitaro Aiyoshi, Yoko Kobayashi, 2014 .

A Method for Design of a Growing Complex Network

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2014 .

A buffer material optimal design in the radioactive wastes geological disposal using the satisficing trade-off method and the self-organizing map

Takashi Okamoto, Eitaro Aiyoshi, Yoko Kobayashi, 2012 .

A Growing Complex Network Design Method

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2011 .

A design method for the complex network growth model

Takashi Okamoto, Hironori Hirata, Seiichi Koakutsu, 2013, The SICE Annual Conference 2013.

A growing complex network design method with an adaptive multi-objective genetic algorithm and an inner link restructuring method

T. Okamoto, H. Mizuno, S. Koakutsu, 2012, 2012 Proceedings of SICE Annual Conference (SICE).

Gamification of the Optimization Problem and Multi-point Type Optimization Methods

Eitaro Aiyoshi, Takashi Okamoto, E. Aiyoshi, 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

Improvement of particle swarm optimization based on the repetitive search guideline

Takashi Okamoto, Eitaro Aiyoshi, Sodo Hiraoka, 2008 .

An Efficiency Improvement of the Equilibrium Solution Search on the Selfish Routing Game by Removing Redundant Paths

Takashi Okamoto, Seiichi Koakutsu, Koichi Yoshida, 2016 .