Title :
A Forecasting Model for Parking Guidance System
Author :
Yong, Sun ; Chunping, Liu ; Yihuai, Wang ; Shukui, Zhang ; Feixiong, Li
Author_Institution :
Inst. of Comput. Sci. & Technol., Soochow Univ., Suzhou, China
fDate :
March 31 2009-April 2 2009
Abstract :
This paper researches prediction problems of Parking Occupancy Rate (POR) for city Parking Guidance System (PGS). First, giving the POR model based on BP Neural Network. Second, discuss the structure of BP Neural Network. At last, make a compare for different BP methods. Experimental results show that the POR predicting BP networkpsilas topology structure is 5-5-1, the generalization capacity is improved highly by combining self-adaptable studying rate and momentum.
Keywords :
backpropagation; forecasting theory; road traffic; traffic control; BP neural network; city parking guidance system; forecasting model; generalization capacity; parking occupancy rate; prediction problem; topology structure; Cities and towns; Computer science; Network topology; Neural networks; Predictive models; Sun; Technology forecasting; Telecommunication traffic; Traffic control; Vehicle dynamics;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.1088
