By Topic

Modeling and prediction of the preparation of hydroxyapatite with sol-gel method by using support vector regression

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Zhao, S. ; Dept. of Appl. Phys., Chongqing Univ., Chongqing, China ; Cai, C.Z. ; Zhu, X.J. ; Wang, G.L.
more authors

A novel modeling approach, support vector regression (SVR) combined with particle swarm optimization (PSO), was employed to construct mathematical model for prediction of the purity and average particle size of hydroxyapatite (HA) based on five synthesis process factors, including the P2O5 content, Ca(NO3)2·4H2O content, aging time, synthesis temperature, and holding time. The accuracy and reliability of the constructed SVR model are validated through the mean absolute percentage error of the leave-one-out cross validation. Then the SVR model is applied to optimize the process parameters. The maximum purity of HA is found to be 98.06% predicted by the SVR model under the optimal synthesis parameters, i.e., the P2O5 content is 1.98 mol/L, Ca(NO3)2·4H2O content is 2.68mol/L, aging time is 17.68h, synthesis temperature is 818.93°C, and holding time is 3.17h. These studies suggest that SVR is an effective and practical methodology to assist the design of experiment, and is helpful to increase the yield and control the average particle size of the synthesized HA via rational process parameters.

Published in:

Nano/Micro Engineered and Molecular Systems (NEMS), 2011 IEEE International Conference on

Date of Conference:

20-23 Feb. 2011