No.
2
Project title: May We Assign Different Values of lambda -Parameter to Attributes for an Extended lambda -Measure?
Adviser: Zhenyuan Wang
Description: The lambda-measure is one of the most important types of monotone measures in common use. It can be adopted to describe a special style of interaction among attributes towards a certain target. The value of the parameter lambda describes the strength of the interaction among predictive attributes towards the target. A certain type of integral with respect to a lambda -measure then can be used as an aggregation tool in information fusion. Recently, some scholars proposed to extend the lambda -measure such that each attribute has own parameter lambda i (i = 1, 2, …, n, where n is the number of predictive attributes). A theoretical analysis is needed to confirm or deny this idea.
References:
[1] M. Sugeno, Theory of Fuzzy Integral and its Applications, Ph. D. dissertation, Tokyo Institute of Technology (1974).
[2] Z. Wang and
G. J. Klir, Fuzzy Measure Theory, Plenum
Press,
[3] S. Yue, P. Li, and Z. Yin, Parameter estimation for Choquet fuzzy integral based on Takagi-Sugeno fuzzy model, Information Fusion 6 (2005) 175-182.
[4] S. Yue, Z. Liu, and P. Wang, An extension of l-measures of Sugeno
applied to data fusion (unpublished).
Prerequisites: MATH 8520/9110.
Requirements: A theoretical analysis and discussion should be made in a research paper that may be submitted to some academic conference.