Title :
An Improved System Cloud Grey Neural Network Model
Author_Institution :
Sch. of Electr. Eng., Beijing Jiaotong Univ., Beijing
Abstract :
This paper improved and optimized the topology structure of the system cloud grey neural network model (SCGNNM (1,1)) and presented a novel SCGNNM (1,1) based on time response model. Because the dispersed data of time response model can be regarded as the data abstracted from the continued function, the model´s precision can be improved greatly. Meantime, the learning algorithm is given. Finally, the proposed model is simulated and shown to be very reliable.
Keywords :
grey systems; learning (artificial intelligence); neural nets; optimisation; topology; SCGNNM; continued function; learning algorithm; system cloud grey neural network model; time response model; topology structure optimization; Cloud computing; Computer networks; Concurrent computing; Genetics; Network topology; Neural networks; Prediction methods; Predictive models; Systems engineering and theory; Time factors; 1); improved SCGNNM (1; neural network; system cloud grey model;
Conference_Titel :
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3334-6
DOI :
10.1109/WGEC.2008.62
