[1] 冯兴杰, 魏新, 黄亚楼. 基于支持向量机回归的旅
客吞吐量预测研究[ J]. 计算机工程, 2005, 31
( 14): 172- 173.
[2] U stun B, M e lssen W J, Oudenhu ijzenM, et a.l Determ
ination o f optim a l support vector reg ression parameters
by genetic a lgo rithm s and simp lex optim iza tion
[ J]. Ana ly tica Ch im ica Ac ta, 2005, 544 ( 1 - 2 ):
292- 305.
[3] Vapn ik V N. Statistica l learning theory [M ]. New
York: JohnW iley & Sons, Inc. , 1998.
[4] Cherkassky V S, M ulier F M. Learning from data:
Concepts, theory, and m ethods [M ]. New York: John
W iley& Sons, 1998.
[5] Cherkassky V, M a Y Q. Practica l se lection of SVM
param eters and noise estim ation fo r SVM regress ion
[ J]. Neu ra lNe tw orks, 2004, 17 ( 1): 113- 126.
[6] 熊伟丽, 徐保国. 基于PSO的SVR参数优化选择方
法研究[ J]. 系统仿真学报, 2006, 18 ( 9): 2 442 -
2 446.
[7] Feng Y, H e Z. Optim ization o f ag itation, aeration, and
tem perature conditions for m ax im um B-m annanase production
[ J]. Enzyme and M icrobia,l 2003, 32 ( 2):
282- 289.
[8] 潘丰. 生化过程智能控制研究[ D] . 无锡: 江南大
学通信与控制工程学院, 2001.
521