Fuzzy modeling approach for integrated assessments using cultural theory

Date

2000-01-01

Author

Yazıcı, Adnan
Pendergraft, C

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

155
views

0
downloads

It has already been noted that predicting societal responses accurately requires the use of a formal model such as cultural theory. A basic belief of cultural theory is that all societies and their underlying worldviews, irrespective of time or place, must be more or less hierarchic, more or less individualistic, more or less egalitarian, or more or less fatalistic. This approach has a potential for cross-temporal and spatial comparisons that makes it a particularly attractive instrument for a study of the human dimensions of global climate change. However, a significant difficulty in the previous attempts for utilizing cultural theory in integrated assessment models (IAMs) has been the inexactness or uncertainty inherent in both IAMs and cultural theory. In this paper we introduce a fuzzy-based modeling approach that makes use of cultural theory in integrated assessment approach to provide a mechanism for understanding the reaction of a populace to environmental policy decisions.

Subject Keywords

Membership function, Fuzzy rule, Integrate assessment, Fuzzy relation, Cultural theory

URI

https://hdl.handle.net/11511/62837

Journal

INTELLIGENT PROBLEM SOLVING: METHODOLOGIES AND APPROACHES, PRODEEDINGS

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Possibilistic interpretation of mistuning in bladed disks by fuzzy algebra Karataş, Hamit Çağlar; Özgüven, Hasan Nevzat; Ciğeroğlu, Ender; Department of Mechanical Engineering (2012) This study aims to define the possibilistic interpretation of mistuning and examine the way of determining the worst case situations and assessing reliability value to that case by using possibilistic methods. Furthermore, in this study, benefits of using possibilistic interpretation of mistuning in comparison to probabilistic interpretation of mistuning are investigated. For the possibilistic analysis of mistuned structures, uncertain mistuning parameters are modeled as fuzzy variables possessing possibili...
Fuzzy versus statistical linear regression Kim, KJ; Moskowitz, H; Köksalan, Mustafa Murat (1996-07-19) Statistical linear regression and fuzzy linear regression have been developed from different perspectives, and thus there exist several conceptual and methodological differences between the two approaches. The characteristics of both methods, in terms of basic assumptions, parameter estimation, and application are described and contrasted. Their descriptive and predictive capabilities are also compared via a simulation experiment to identify the conditions under which one outperforms the other. It turns out...
Appropriateness of a cognitive approach to Donald Davidson's meaning theory Ağoğlu, Eser; Sayan, Erdinç; Department of Philosophy (2008) The purpose of this study is to discuss the appropriateness of a cognitive approach to Donald Davidson's meaning theory. Davidson makes the bold proposal that a truth theory, modified for a natural language, may be treated as a meaning theory for that language. According to Davidson, a meaning theory is an empirical theory. Radical Interpretation is at the center of such an empirical inquiry which places restrictions on the truth theory to make it suitable as a meaning theory without appeal to semantic noti...
Decision fusion for supervised, unsupervised and semi-supervised learnings Özay, Mete; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2013) In this thesis, Decision Fusion approaches have been analyzed for Supervised, Unsupervised and Semi-supervised Learning problems. In Supervised Learning, classification or generalization error minimization problem has been studied by analyzing the classification error of a classification algorithm into two parts. In the first part, the minimization of the difference between N-sample and large-sample classification error of k-NN has been studied using a hierarchical decision fusion algorithm called Fuzzy Sta...
Fuzzy classification models based on tanaka’s fuzzy linear regression approach and nonparametric improved fuzzy classifier functions Özer, Gizem; Köksal, Gülser; Department of Industrial Engineering (2009) In some classification problems where human judgments, qualitative and imprecise data exist, uncertainty comes from fuzziness rather than randomness. Limited number of fuzzy classification approaches is available for use for these classification problems to capture the effect of fuzzy uncertainty imbedded in data. The scope of this study mainly comprises two parts: new fuzzy classification approaches based on Tanaka’s Fuzzy Linear Regression (FLR) approach, and an improvement of an existing one, Improved Fu...

Citation Formats

A. Yazıcı and C. Pendergraft, “Fuzzy modeling approach for integrated assessments using cultural theory,” INTELLIGENT PROBLEM SOLVING: METHODOLOGIES AND APPROACHES, PRODEEDINGS, pp. 250–259, 2000, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62837.