RBF neural network soft-sensor modeling of rotary kiln pellet quality indices optimized by biogeography-based optimization algorithm

Journal of Chemical Engineering of Japan

Volumn 48, Issue 1, 2015, Pages 7-15

  Wang, Jie Sheng ^a   Shen, Na Na ^a   Ren, Xiu Dong ^a   Liu, Guan Nan ^b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY LIAONING   (China)

^b Liaoning Anshan Power Supply Company   (China)

Author keywords

Biogeography based optimization algorithm; RBF neural network; Rotary kiln pellet sintering; Soft sensor

Indexed keywords

CHAINS; ECOLOGY; HEURISTIC ALGORITHMS; INDICATORS (CHEMICAL); OPTIMIZATION; PELLETIZING; RADIAL BASIS FUNCTION NETWORKS; REAL TIME CONTROL; ROTARY KILNS; SINTERING;

BIOGEOGRAPHY-BASED OPTIMIZATION ALGORITHMS; BIOGEOGRAPHYBASED OPTIMIZATIONS (BBO); CHEMICAL COMPOSITIONS; METALLURGICAL PROPERTIES; MULTIPLE INPUT SINGLE OUTPUTS; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NEURAL NETWORK; SOFT SENSORS;

ALGORITHMS;

EID: 84921652269     PISSN: 00219592     EISSN: None     Source Type: Journal    
DOI: 10.1252/jcej.14we135     Document Type: Article

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