Publicação: Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks
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2011-10-24
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Resumo
The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.
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Artificial Neural Network, Feature Reduction, Fuzzy Sets, Rough Sets, Traffic Breakdown, Dynamic routing, Feature reduction, Flow process, Fuzzy inference mechanism, Fuzzy networks, Fuzzy relations, Human expert, Metropolitan area, Multi layer perceptron, Neuro-fuzzy network, Radial basis functions, Rough set, Rough Sets Theory, Routing performance, Routing process, Rule basis, Surface response, Technological improvements, Traffic behavior, Traffic flow breakdown, Traffic parameters, Dynamics, Forecasting, Fuzzy inference, Fuzzy set theory, Fuzzy sets, Membership functions, Radial basis function networks, Rough set theory, Traffic control, Neural networks
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Inglês
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Proceedings of the International Joint Conference on Neural Networks, p. 1943-1947.
