Open AccessEVALUATING THE URBAN PUBLIC TRANSIT NETWORK BASED ON THE ATTRIBUTE RECOGNITION MODEL
Author(s) -
Qizhou Hu,
Huapu Lu,
Wu Deng
Publication year - 2010
Publication title -
transport
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 31
eISSN - 1648-4142
pISSN - 1648-3480
DOI - 10.3846/transport.2010.37
Subject(s) - reliability (semiconductor) , public transport , computer science , transit (satellite) , measure (data warehouse) , data mining , linkage (software) , variety (cybernetics) , government (linguistics) , mode (computer interface) , transport engineering , machine learning , artificial intelligence , engineering , human–computer interaction , power (physics) , biochemistry , physics , chemistry , linguistics , philosophy , quantum mechanics , gene
The aim of this paper is to propose an attribute recognition model, so that it can be used to simultaneously estimate the public transit network system. Based on the analysis of a variety of factors influencing the public transit network, quantitative research has been conducted with reference to the attribute recognition theory in order to make scientific decision‐making. On the basis of defining attribute measure, this paper presents the attribute recognition model suggesting the attribute recognition theory that can be used to evaluate the public transit network. The reliability of the new method can be explained using real data of the survey on the public transit network in China. The applied results offer scientific reference for instructing and controlling urban traffic by the Government. The main advantages of the new model are in contexts where internal linkage and shared inputs between activities can be considered. The structure of this mode is more realistic than that of the conventional one.