Abstract
A decision tree is a method you can use to help make good choices, especially decisions that involve high costs and risks. Decision trees use a graphic approach to compare competing alternatives and assign values to those alternatives by combining uncertainties, costs, and payoffs into specific numerical values. A fuzzy decision tree is a generalization of the crisp case. Fuzzy decision trees are helpful for representing ill-defined structures in decision analysis. This chapter presents investment analyses using fuzzy decision trees with examples.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Boyen, X.: Design of fuzzy logic-based decision trees applied to power system transient stability assessment. Master’s Thesis, University of Liège (1995)
Canada, J.R., White, J.A.: Capital investment decision analysis for management and engineering. Prentice-Hall, Englewood Cliffs (1980)
Chen, R.Y., Sheu, D.D., Liu, C.M.: Vague knowledge search in the design for outsourcing using fuzzy decision tree. Computers & Operations Research 34, 3628–3637 (2007)
Heinz, A.P.: Pipelined neural tree learning by error forward-propagation. ICNN 1995. In: Proceedings of the IEEE International Conference on Neural Networks (1995)
Malcolm, J.B., Michael, J.P., Yu-Cheng, T.: The application of fuzzy decision tree analysis in an exposition of the antecedents of audit fees. Omega 32, 231–244 (2004)
Odejobi, O.A., ShunHa, S.W., Anthony, J.B.: A fuzzy decision tree-based duration model for Standard Yoruba text-to-speech synthesis. Computer Speech and Language 21, 325–349 (2007)
Savsek, T., Vezjak, M., Pavesic, N.: Fuzzy trees in decision support systems. European Journal of Operational Research 174, 293–310 (2006)
Scharer, M., Page, T., Beven, K.: A fuzzy decision tree to predict phosphorus export at the catchment scale. Journal of Hydrology 331, 484–494 (2006)
Wang, X., Chen, B., Qian, G., Ye, F.: On the optimization of fuzzy decision trees. Fuzzy Sets and Systems 112, 117–125 (2000)
Xizhao, W., Bin, C., Guoliang, Q., Feng, Y.: On the optimization of fuzzy decision trees. Fuzzy Sets and Systems 112, 117–125 (2000)
Yuan, Y., Shaw, M.J.: Induction of fuzzy decision trees. Fuzzy Sets and Systems 69, 125–139 (1995)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Kahraman, C. (2008). Investment Analyses Using Fuzzy Decision Trees. In: Kahraman, C. (eds) Fuzzy Engineering Economics with Applications. Studies in Fuzziness and Soft Computing, vol 233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70810-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-70810-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70809-4
Online ISBN: 978-3-540-70810-0
eBook Packages: EngineeringEngineering (R0)