Application Of Fuzzy Measures Research Articles

NON-ADDITIVE MULTIPLE CRITERIA APPROACH FOR THE EVALUATION OF INTERNATIONAL CLIMATE THINK TANKS

This paper outlines the application of non-additive measures and Choquet integral in the construction of a composite indicator to assess the performance of international climate think tanks and evaluate their influence in shaping climate policies and raising awareness among the general public. The composite index consists of 15 carefully selected indicators according to the feedback provided by Experts within the field and structured into three main pillars: Activities, Publications and Dissemination. In order compare Think Tanks of different size and hence to measure their efficiency, the standardized ranking is also computed dividing the Think Tank outcome in each criterion by the number of its researchers. The application of fuzzy measures and Choquet integral, allowing to take into account potential interactions existing among criteria, increases substantially the model capability both in eliciting effectively Experts’ preferences and in aggregating indicators. Moreover, we present a novel technique for the aggregation of Experts’ preferences where Decision Makers’ weights have been set proportionally to their consistency in evaluating the specific questionnaire.

The Ex-Ante Evaluation of Achieving Sustainable Development Goals

This paper describes the methodology and main results from an overall assessment on future achievement of sustainable development goals. The proposed approach consists of a model-based, looking forward composite sustainable development index—FEEM sustainability index—projected to the future. It represents a first experiment to reproduce the future dynamics of sustainable development indicators over time and worldwide and to assess future sustainability under different scenarios. The assessment presented here is relevant under different viewpoints. First, it has a very broad nature in terms of both geographical coverage and meaningfulness: it considers the multi-dimensional structure of sustainable development by combining relevant indicators belonging to economic, social and environmental pillars for the whole world. Second, the modelling framework to compute future trends of indicators relies upon a recursive-dynamic computable general equilibrium model. This is an ideal tool to look simultaneously at the development of many indicators, their potential interactions and trade-offs, and more in general to the consequences of economic development and/or policies aiming to increase performance in one or more indicators; it allows measuring the overall sustainability under alternative scenarios, across countries and over time. Finally, regarding the construction of the composite indicator, the application of fuzzy measures and Choquet integral increases substantially the model capability allowing taking into account the interactions that exist among the three main pillars of sustainability and the considered indicators.

К вопросу о практическом применении нечетких мер и интеграла Шоке

К вопросу о практическом применении нечетких мер и интеграла Шоке

Application of fuzzy measures in the product appearance value assessment

This paper presents a fuzzy approach to identifying product appearance value. The proposed approach has been developed from fuzzy assessment methods in the literature and applied to the MP3 player. Highly subjective judgments and ambiguity regarding the presence of values and the product type of the appearance resulting from these values suggest the usefulness the fuzzy approach. Where the uncertainty arises from the inability to perform adequate measurements, fuzzy sets provide a mathematical method for representing such uncertainties. Applying the fuzzy approach, product appearance values which are common, and should be common in the MP3 player, are identified and these values are organized into six generic value types: (1) communication of aesthetic, (2) symbolic, (3) functional, (4) ergonomic information, (5) attention drawing, and (6) categorization. Finally the uncertainties of the appearance value sets are quantified by the measure of fuzzy entropy.

Application of fuzzy measures and interval computation to financial portfolio selection

As many data-driven fields, finance is rich in problems requiring high computational power and intelligent systems techniques. In particular, the problem of selecting an optimal financial portfolio can be conveniently represented as a constrained optimization problem or a decision-making problem. The aim of this paper is to show how to express the optimal portfolio selection problem from a decision-theoretic perspective and show how to address this problem using fuzzy measures and fuzzy integrals. © 2010 Wiley Periodicals, Inc.

ファジィ測度の応用としてのファジィ・タイミング・パスワード

ファジィ測度の応用としてのファジィ・タイミング・パスワード

Modeling attitude to risk in human decision processes: An application of fuzzy measures

Several models of the human decision process have been proposed, classical examples of which are utility theory and prospect theory. In recent times, the theory of fuzzy measures and integrals has emerged as an alternative meriting further investigation. Specifically, one is interested in the degrees of disjunction and conjunction and the veto and favor indices that represent the tolerance measure of the decision maker. Though several theoretical expositions have appeared in contemporary literature, empirical studies applying these concepts to the real world are scarce. This paper reports two studies based on a model of strategic telecommunication investment decisions from a research work involving a survey of executives. The first study involves building fuzzy models corresponding to each individual decision maker with the results grouped based on the decision makers’ propensity to risk as determined by their degrees of disjunction. The Shapley indices and the interaction effects are determined for each pooled dataset corresponding to each group. To contrast this approach with those of conventional nomothetic comparisons of decision policies, the decision makers are grouped based on a clustering analysis of the individual linear regression models. The data for each cluster are pooled and the fuzzy measures learned from the dataset are analyzed for comparison purposes. The results not only serve as a demonstration of fuzzy measure analysis as a viable approach to studying qualitative decision making but also provide useful methodological insights into applying fuzzy measures to strategic investment decisions under risk.

Application of Fuzzy Measure in Classification of Childhood Bronchial Asthma

Application of Fuzzy Measure in Classification of Childhood Bronchial Asthma