|
|
|
|
|
Jiayu Wen, Yanguo Song, Huanjin Wang, Dong Han and Changfa Yang
Neural networks have been widely used as compensational models for aircraft control designs and as surrogate models for other optimizations. In the case of tiltrotor aircraft, the total number of aircraft states and controls is much greater than that of ...
ver más
|
|
|
|
|
|
|
|
|
Daniel S. Soper
When designed correctly, radial basis function (RBF) neural networks can approximate mathematical functions to any arbitrary degree of precision. Multilayer perceptron (MLP) neural networks are also universal function approximators, but RBF neural networ...
ver más
|
|
|
|
|
|
|
|
|
Vladimir Milic, Josip Kasac and Marin Lukas
This paper presents an approach for the solution of a zero-sum differential game associated with a nonlinear state-feedback H8
H
8
control problem. Instead of using the approximation methods for solving the corresponding Hamilton?Jacobi?Isaacs (HJI) par...
ver más
|
|
|
|
|
|
|
|
|
Jiajia Fan, Wentao Huang, Qingchao Jiang and Qinqin Fan
For multimodal multi-objective optimization problems (MMOPs), there are multiple equivalent Pareto optimal solutions in the decision space that are corresponding to the same objective value. Therefore, the main tasks of multimodal multi-objective optimiz...
ver más
|
|
|
|
|
|
|
|
|
Levente Fazekas, Boldizsár Tüu-Szabó, László T. Kóczy, Olivér Hornyák and Károly Nehéz
Flow-shop scheduling problems are classic examples of multi-resource and multi-operation scheduling problems where the objective is to minimize the makespan. Because of the high complexity and intractability of the problem, apart from some exceptional ca...
ver más
|
|
|
|