Pages that link to "Item:Q1126664"

The following pages link to Approximating polynomial functions by feedforward artificial neural networks: Capacity analysis and design (Q1126664):

Displaying 9 items.

• Training feedforward neural networks using hybrid particle swarm optimization and gravitational search algorithm (Q387497) (← links)
• Solving group technology problems via clique partitioning (Q877223) (← links)
• The essential order of simultaneous approximation for neural networks (Q990650) (← links)
• Generalized polynomial decomposable multiple attribute utility functions for ranking and rating multiple criteria discrete alternatives. (Q1569102) (← links)
• Training artificial neural networks by a hybrid PSO-CS algorithm (Q1736659) (← links)
• Extremist vs. centrist decision behavior: Quasi-convex utility functions for interactive multi-objective linear programming problems (Q1867097) (← links)
• Determining functional relationships from trained neural networks (Q1900310) (← links)
• A deep learning approach for efficiently and accurately evaluating the flow field of supercritical airfoils (Q2289636) (← links)
• Mapping polynomial fitting into feedforward neural networks for modeling nonlinear dynamic systems and beyond (Q2495806) (← links)