135 resultados para Rating aggregation

em Deakin Research Online - Australia


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Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision that are ever present in decision support and expert systems in many areas. The choice of aggregation operators is crucial to the behavior of the system that is intended to mimic human decision making. This paper discusses how aggregation operators can be selected and adjusted to fit empirical data—a series of test cases. Both parametric and nonparametric regression are considered and compared. A practical application of the proposed methods to electronic implementation of clinical guidelines is presented

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The need for monotone approximation of scattered data often arises in many problems of regression, when the monotonicity is semantically important. One such domain is fuzzy set theory, where membership functions and aggregation operators are order preserving. Least squares polynomial splines provide great flexbility when modeling non-linear functions, but may fail to be monotone. Linear restrictions on spline coefficients provide necessary and sufficient conditions for spline monotonicity. The basis for splines is selected in such a way that these restrictions take an especially simple form. The resulting non-negative least squares problem can be solved by a variety of standard proven techniques. Additional interpolation requirements can also be imposed in the same framework. The method is applied to fuzzy systems, where membership functions and aggregation operators are constructed from empirical data.

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This article discusses a range of regression techniques specifically tailored to building aggregation operators from empirical data. These techniques identify optimal parameters of aggregation operators from various classes (triangular norms, uninorms, copulas, ordered weighted aggregation (OWA), generalized means, and compensatory and general aggregation operators), while allowing one to preserve specific properties such as commutativity or associativity. © 2003 Wiley Periodicals, Inc.

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This paper treats the problem of fitting general aggregation operators with unfixed number of arguments to empirical data. We discuss methods applicable to associative operators (t-norms, t-conorms, uninorms and nullnorms), means and Choquet integral based operators with respect to a universal fuzzy measure. Special attention is paid to k-order additive symmetric fuzzy measures.

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Agent technology provides a new way to model many complex problems like financial investment planning. With this observation in mind, a financial investment planning system was developed from agent perspectives with 12 different agents integrated. Some of the agents have similar problem solving and decision making capabilities. The results from these agents require to be combined. Ordered Weighted Averaging (OWA) operator was chosen to aggregate different results. Details on how OWA was applied as well as appropriate evaluation are presented.

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Environmental performance assessment or green building rating tools for commercial buildings are one of the more recent responses to encourage green solutions for commercial buildings. This paper discusses the initial stages of a research project that looks at the impact of a rating tool, such as Green Star, on design. There are numerous ways in which an architect can design commercial buildings, but environmental design solutions have consistently failed to become accepted practice. Therefore, how will this tool be incorporated into the building design process? Developed to assist the designer can the inclusion of a rating tool such as Green Star provide an effective framework to encourage the inclusion of environmental design strategies in commercial buildings? A field study, recording the design process of a commercial building, anticipates that a whole building assessment approach towards design, as proposed through the Green Star Rating Tool, will provide an effective framework to set and monitor design targets in order to optimise the environmental design goals in commercial buildings.

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Aggregation operators model various operations on fuzzy sets, such as conjunction, disjunction and averaging. Recently double aggregation operators have been introduced; they model multistep aggregation process. The choice of aggregation operators depends on the particular problem, and can be done by fitting the operator to empirical data. We examine fitting general aggregation operators by using a new method of monotone Lipschitz smoothing. We study various boundary conditions and constraints which determine specific types of aggregation.

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Aggregation operators model various operations on fuzzy sets, such as conjunction, disjunction and aver aging. The choice of aggregation operators suitable for a particular problem is frequently done by fitting the parameters of the operator to the observed data. This paper examines fitting general aggregation operators by using a new method of Lipschitz approximation.

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We propose a generalization of the notion of the absorbent element of aggregation operators. Our construction involves tuples of values that are absorbent, that is, that decide the result of aggregation. We analyze some basic properties of this generalization and determine the absorbent tuples of some popular classes of aggregation operators.

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This paper establishes tight upper and lower bounds on Lipschitz aggregation operators considering their diagonal, opposite diagonal and marginal sections. Also we provide explicit formulae to determine the bounds. These are useful for construction of these type of aggregation operators, especially using interpolation schemata.

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We generalize the notion of a neutral element of aggregation operators. Our construction involves tuples of values that are neutral with respect to the result of aggregation. Neutral tuples are useful to model situations in which information from different sources, or preferences of several decision makers, cancel each other. We examine many popular classes of aggregation operators in respect to their neutral sets, and also construct new aggregation operators with predefined neutral sets