| APPLICATION OF BIONIC ALGORITHM BASED ON CS-SVR AND BA-SVR IN SHORT-TERM TRAFFIC STATE PREDICTION MODELING OF URBAN ROAD
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| Yun Zhu , Chengwenyuan Huang , Yang Wang , Jianyu Wang |
| School of Automation, Nanjing University of Science and Technology |
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| ABSTRACT |
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Accurate short-term traffic state prediction is a crucial requisite for control and guidance of traffic flow in the
intelligent traffic system, which has attracted increasing attention in the transportation field recently. This paper tests the
optimization performances of two emerging bionic algorithms, known as Cuckoo Search Algorithm (CS) and Bat Algorithm
(BA). Combined with the Support Vector Regression (SVR) principle, the two aforementioned algorithms are applied to
optimize the kernel function parameters in SVR. At last, the speed data of a road network in Guangzhou are collected. The
prediction performances of the CS-SVR and BA-SVR models are tested after preprocessing the data. From the overall
prediction rates, the CS-SVR algorithm is slightly better than BA-SVR in terms of calculating speed. Furthermore, the two
algorithms are significantly superior to the traditional SVR model and long short-term memory networks (LSTM), thereby
verifying their effectiveness and practicability in short-term traffic state prediction. |
| Key Words:
Intelligent traffic system, Traffic state prediction, Cuckoo search algorithm, Bat algorithm
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Corresponding Author.
Yun Zhu , Email. 
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