Application of Particle Swarm Optimization to the Mixed Discrete Non-Linear Problems. - Satoshi Kitayama; Koetsu Yamazaki; Masao Arakawa (AIAI, 2005)

A Method for the Mixed Discrete Non-Linear Problems by Particle Swarm Optimization. - Satoshi Kitayama; Masao Arakawa; Koetsu Yamazaki (System Modelling and Optimization, 2005)

Differential evolution as the global optimization technique and its application to structural optimization. - Satoshi Kitayama; Masao Arakawa; Koetsu Yamazaki (Appl. Soft Comput., 2011)

Simple estimate of the width in Gaussian kernel with adaptive scaling technique. - Satoshi Kitayama; Koetsu Yamazaki (Appl. Soft Comput., 2011)

Sequential approximate optimization for discrete design variable problems using radial basis function network. - Satoshi Kitayama; Masao Arakawa; Koetsu Yamazaki (Appl. Math. Comput., 2012)

Compromise point incorporating trade-off ratio in multi-objective optimization. - Satoshi Kitayama; Koetsu Yamazaki (Appl. Soft Comput., 2012)

Development of Energy Management of Hybrid Electric Vehicle for Improving Fuel Consumption via Sequential Approximate Optimization. - Ryuhei Hagura; Satoshi Kitayama (J. Robotics Mechatronics, 2014)

Multi-objective optimization of volume shrinkage and clamping force for plastic injection molding via sequential approximate optimization. - Satoshi Kitayama; Shinji Natsume (Simul. Model. Pract. Theory, 2014)

Numerical and experimental investigation of process parameters optimization in plastic injection molding using multi-criteria decision making. - Satoshi Kitayama; Yusuke Yamazaki; Masahiro Takano; Shuji Aiba (Simul. Model. Pract. Theory, 2018)

Time Series Prediction Using Radial Basis Function Network with Transformation of Training Data and Its Applications. - Satoshi Kitayama; Kohei Saito (Autom. Control. Comput. Sci., 2022)

Numerical optimization of baffle configuration in header of heat exchanger using sequential approximate optimization. - Satoshi Kitayama; Kohei Miyamoto; Rihito Izutsu; Satoshi Tabuchi; Sayaka Yamada (Simul. Model. Pract. Theory, 2022)