Fuzzy Combination Forecasting of Urban Transit Demand

Article Preview

Abstract:

Based on the analysis of the existing forecasting methods of the urban public transit demand scale and concerning the characteristics of urban public transit demand forecasting, this paper introduces the concept of triangular fuzzy number and puts forward the fuzzy combination forecasting methods in terms of political factors. Following that, steps and process to implement the fuzzy combination forecasting are further expounded, and specific examples are adopted to prove the feasibility and validity of the method.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1808-1812

Citation:

Online since:

March 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Suparta W, Alhasa K M: Expert Systems with Applications, 42(2015), 1050. J.

Google Scholar

[2] Li JM, Li P: Applied Mechanics and Materials, 543(2014), 869. J.

Google Scholar

[3] Wang MP, Tian Q, Zhang J, Jin NN: Journal of Applied Sciences, 13(2013), 1911. J.

Google Scholar

[4] Li GN, Shan MY: Journal of Central South University, 44(2013), 4542. J.

Google Scholar

[5] Egrioglu E, Aladag, CH, Yolcu U: Expert Systems with Applications, 40(2013), 854. J.

Google Scholar

[6] Che JX, Wang JZ, Wang GF: Energy, 37(2012)657. J.

Google Scholar

[7] Hung JC: Applied Soft Computing, 11(2011)3938. J.

Google Scholar

[8] Stathopoulos A, Karlaftis MG: Transportation Research Record, 2183(2010), 120. J.

Google Scholar

[9] Wang FK, Chang KK: Expert Systems with Applications, 37(2010), 8119. J.

Google Scholar