應用類神經網路和基因演算法求解最佳參數設計
全文
相關文件
In this paper, we have studied a neural network approach for solving general nonlinear convex programs with second-order cone constraints.. The proposed neural network is based on
Then, based on these systematically generated smoothing functions, a unified neural network model is pro- posed for solving absolute value equationB. The issues regarding
Using this formalism we derive an exact differential equation for the partition function of two-dimensional gravity as a function of the string coupling constant that governs the
Courtesy: Ned Wright’s Cosmology Page Burles, Nolette & Turner, 1999?. Total Mass Density
This kind of algorithm has also been a powerful tool for solving many other optimization problems, including symmetric cone complementarity problems [15, 16, 20–22], symmetric
3. Works better for some tasks to use grammatical tree structure Language recursion is still up to debate.. Recursive Neural Network Architecture. A network is to predict the
Moreover, this chapter also presents the basic of the Taguchi method, artificial neural network, genetic algorithm, particle swarm optimization, soft computing and
This study proposed the Minimum Risk Neural Network (MRNN), which is based on back-propagation network (BPN) and combined with the concept of maximization of classification margin