摘要
An improved RBFN algorithm is proposed.Its training algorithm includes K-mean cluster algorithm and improved recursive method with discounted measurements.The former is used in on-line leaming network centers,and the latter is used to adjust netword weights.Simulation results about estimating the catalyst activity in an industrial fixed-bed reactor show that the training algorithm provides simple structure,good track performance,fast learning speed.
An improved RBFN algorithm is proposed.Its training algorithm includes K-mean cluster algorithm and improved recursive method with discounted measurements.The former is used in on-line leaming network centers,and the latter is used to adjust netword weights.Simulation results about estimating the catalyst activity in an industrial fixed-bed reactor show that the training algorithm provides simple structure,good track performance,fast learning speed.
出处
《化工学报》
EI
CAS
CSCD
北大核心
1998年第6期755-759,共5页
CIESC Journal
基金
国家自然科学基金!No.69474030
关键词
RBFN
固定床反应器
催化剂
活性系数
估计
radial basis function network（RBFN),fixed-bed reactor,catalyst activity coefficient
