Choquet fuzzy integral-based hierarchical networks for decision analysis

Research output: Contribution to journalArticlepeer-review

94 Citations (Scopus)


A Choquet fuzzy integral-based approach to hierarchical network implementation is investigated. In this approach, we generalized the fuzzy integral as an excellent component for decision analysis. The generalization involves replacing the max (or min) operator in information aggregation with a fuzzy integral-based neuron, resulting in increased flexibility. The characteristics of the Choquet fuzzy integral are studied and a network-based decision-analysis framework is proposed. The trainable hierarchical network can be implemented utilizing the fuzzy integral-based neurons and connectives. The training algorithms are derived and several examples given to illustrate the behaviors of the networks. Also, we present a decision making experiment using the proposed network to learn appropriate functional relationships in the defective numeric fields detection domain.

Original languageEnglish
Pages (from-to)63-71
Number of pages9
JournalIEEE Transactions on Fuzzy Systems
Issue number1
Publication statusPublished - 1999

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


Dive into the research topics of 'Choquet fuzzy integral-based hierarchical networks for decision analysis'. Together they form a unique fingerprint.

Cite this