• Corpus ID: 117265288

Fuzzy Measures and Integrals: Theory and Applications

  title={Fuzzy Measures and Integrals: Theory and Applications},
  author={Michel Grabisch and Michio Sugeno and Toshiaki Murofushi},
P. Wakker: Foreword.- M. Grabisch, T. Murofushi, M. Sugeno: Preface.- Theory: T. Murofushi, M. Sugeno: Fuzzy Measures and Fuzzy Integrals.- D. Denneberg: Non-additive Measure and Integral, Basic Concepts and Their Role for Applications.- M. Grabisch: The Interaction and Mobius Representations of Fuzzy Measures on Finite Spaces, k-Additive Measures: A Survey.- K. Fujimoto, T. Murofushi: Hierarchical Decomposition of the Choquet Integral.- I. Kramosil: Towards Generalized Belief Functions.- G. De… 
Ternary Kleenean non-additive measures
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Monotone Measures-Based Integrals
This chapter summarizes basic types of monotone measures together with the basic monot one measures-based integrals, and the concept of universal integrals proposed by Klement etal to give a common roof for all mentioned integrals are introduced.
Sugeno fuzzy integral generalizations for Sub-normal Fuzzy set-valued inputs
This article discusses a direct generalization of the Sugeno FI for sub-normal FS integrands and numeric FMs, called the Sub-normal Fuzzy Integral (SuFI).
Generalization of the Fuzzy Integral for discontinuous interval- and non-convex interval fuzzy set-valued inputs
The Fuzzy Integral (FI) is a powerful approach for non-linear data aggregation. It has been used in many settings to combine evidence (typically objective) with the known “worth” (typically
A Universal Integral as Common Frame for Choquet and Sugeno Integral
This work provides a concept of integrals generalizing both the Choquet and the Sugeno case, and introduces and investigates universal integrals, which can be defined on arbitrary measurable spaces and for arbitrary monotone measures.
A Conjoint Measurement Approach to the Discrete Sugeno Integral
The connections between the discrete Sugeno integral and a non-numerical model called the noncompensatory model are studied and it is shown that the main condition used in the result of S. Greco, B. Matarazzo and R. Sowi´ nski can be factorized in such a way that the discrete sugarseno integral model can be viewed as a particular case of a general decomposable representation.
Fuzzy Measures and Integrals in MCDA
This chapter aims at a unified presentation of various methods of MCDA based onfuzzy measures (capacity) and fuzzy integrals, essentially the Choquet andSugeno integral. A first section sets the
Approximating fuzzy measures by hierarchically decomposable ones
  • J. Domingo-Ferrer, V. Torra
  • Computer Science
    Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)
  • 2002
This work proposes a method to approximate a general fuzzy measure by a Hierarchically Decomposable one (one type of fuzzy measure of reduced complexity).
New Fuzzy Aggregations . Part II : Associated Probabilities in the Aggregations of the POWA operator
Several variants of the generalizations of the fuzzy-probabilistic OWA operator POWA are presented in the environment of fuzzy uncertainty, where different monotone measures (fuzzy measure) are used as an uncertainty measure.