[1]CHEN Liang,HE Wei,HAN Liqun.Radial basis function neural network modeling of the traffic path cost function[J].CAAI Transactions on Intelligent Systems,2011,6(5):424-431.
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Radial basis function neural network modeling of the traffic path cost function

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 5 Page number: 424-431 Column: 学术论文—人工智能基础 Public date: 2011-10-30
Title:
Radial basis function neural network modeling of the traffic path cost function
Author(s):
CHEN Liang;  HE Wei;  HAN Liqun
College of Computer and Information Engineering, Beijing Commercial and Industrial University, Beijing 100048, China
Keywords:
intelligent transportation;  path cost function;  vehicle route optimization;  radial basis function neural network;  graph theory
CLC:
TP391.4
DOI:
-
Abstract:
Vehicle route optimization is one of the hot topics in research on urban intelligent transportation systems (ITS), and it plays an important role in the optimization of the entire transportation system. This paper analyzed various factors that affect the travel time and established a path cost function model with an radial basis function neural network, based on the shortest paths algorithms in graph theory. By this function model, the timeoriented optimal path between any two given places on a traffic map can be calculated. The model was applied to actual traffic to validate the effectiveness, and its results are of practical value, showing the correctness and validity of the model.
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