Kernel partial least squares based on least squares support vector machine primal-dual optimization problem;

A new algorithm for solving inequality constraint optimization problem;

The Study and Empirical Analysis of Neural Network Methods for Optimization Problems;

In this paper, a new generalized gradient projection method with inexact line search is proposed for the nonlinear optimization problem with linear constraints.

For analysing and studing the characteristic and optimized mechanism of transient chaotic neural network,based on analysis of transient chaotic neuron model,through programming the simulation analysis in the Matlab software to compare the neural network dynamic characteristic and various parameters regarding the network optimization process influence.

In this section of the paper,we summarize statistical simulation problem and provide the simulation algorithms of statistics distribution,large sample simulation,testing power,empirical simulation and optimal problem,etc.

Research on Algorithm Pattern of Optimization Problems;

In this paper,the hausdorff distance between the epigraphs of the two functions defines the distance between object ice functions in optimization problems.

It is given that a superlinearly convergent feasible direction method for solving optimization problems with lincar constraints.