Response surface model development for global/local optimization using radial basis functions

2000 ◽  
Author(s):  
Dale McDonald ◽  
Walter Grantham ◽  
Wayne Tabor ◽  
Michael Murphy
Keyword(s):  
Response Surface ◽  
Radial Basis Functions ◽  
Model Development ◽  
Local Optimization ◽  
Response Surface Model ◽  
Basis Functions ◽  
Surface Model ◽  
Radial Basis

Response Surface Based Cost Model for Onshore Wind Farms Using Extended Radial Basis Functions

2010 ◽  
Author(s):  
Jie Zhang ◽  
Souma Chowdhury ◽  
Achille Messac ◽  
Luciano Castillo ◽  
Jose Lebron
Keyword(s):  
Response Surface ◽  
Radial Basis Functions ◽  
Wind Farm ◽  
Cost Model ◽  
Wind Farms ◽  
Labor Cost ◽  
Basis Functions ◽  
Onshore Wind ◽  
Radial Basis ◽  
The Cost

This paper develops a cost model for onshore wind farms in the U.S.. This model is then used to analyze the influence of different designs and economic parameters on the cost of a wind farm. A response surface based cost model is developed using Extended Radial Basis Functions (E-RBF). The E-RBF approach, a combination of radial and non-radial basis functions, can provide the designer with significant flexibility and freedom in the metamodeling process. The E-RBF based cost model is composed of three parts that can estimate (i) the installation cost, (ii) the annual Operation and Maintenance (O&M) cost, and (iii) the total annual cost of a wind farm. The input parameters for the E-RBF based cost model include the rotor diameter of a wind turbine, the number of wind turbines in a wind farm, the construction labor cost, the management labor cost and the technician labor cost. The accuracy of the model is favorably explored through comparison with pertinent real world data. It is found that the cost of a wind farm is appreciably sensitive to the rotor diameter and the number of wind turbines for a given desirable total power output.

A FAST METHOD FOR IMPLICIT SURFACE RECONSTRUCTION BASED ON RADIAL BASIS FUNCTIONS NETWORK FROM 3D SCATTERED POINTS

2007 ◽  
Vol 17 (06) ◽  
pp. 459-465 ◽  
Author(s):  
HANBO LIU ◽  
XIN WANG ◽  
WENYI QIANG
Keyword(s):  
Uniform Distribution ◽  
Radial Basis Functions ◽  
Surface Reconstruction ◽  
Basis Function ◽  
Basis Functions ◽  
Surface Model ◽  
Fast Method ◽  
Feature Points ◽  
Implicit Surface ◽  
Radial Basis

A method for arbitrary surface reconstruction from 3D large scattered points is proposed in this paper. According to the properties of 3D points, e.g. the non-uniform distribution and unknown topology, an implicit surface model is adopted based on radial basis functions network. And because of the property of locality of radial basis function, the method is fast and robust in surface reconstruction. Furthermore, an adapted K-Means algorithm is used to reduce reconstruction centers. For features completeness, two effective methods are introduced to extract the feature points before the adapted K-Means algorithm. Experiment results show that the presented approach is a good solution for reconstruction from 3D large scattered points.

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