Since much of human reasoning is based on imprecise, vague and subjective values, most of decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Zadeh’s (Zadeh 1965) fuzzy logic has given analysts a tool to present the human behavior more precisely, especially where relatively few data exist, and where the expert knowledge about the system is vague and lingui...

Humans think and talk about regions and spatial relations imprecisely, in terms of vague concepts that are fuzzy or probabilistic (e.g., downtown, near). The functionality of geographic information systems will be increased if they can interpret vague queries. We discuss traditional and newer approaches to defining and modeling spatial queries. Most of the research on vague concepts in informat...

By the development of Semantic Web, increasing demands for vague information representation have triggered a mass of theoretical and applied researches of fuzzy ontologies, whose main logical infrastructures are fuzzy description logics. However, current tableau algorithms can not supply complete reasoning support within fuzzy ontology: reasoning with general TBox is still a difficult problem i...

Fuzzy decision making is the collection of single or multicriteria techniques aiming at selecting the best alternative in case of imprecise, incomplete, and vague data. This chapter reviews the fuzzy decision making literature and summarizes the review results by tabular and graphical illustrations. The classification is based on the new extensions of fuzzy sets: Intuitionistic, hesitant, and t...

In many geographical applications there is a need to model spatial phenomena not simply by sharply bounded objects but rather through vague concepts due to indeterminate boundaries. Spatial database systems and geographical information systems are currently not able to deal with this kind of data. In order to support these applications , for an important kind of vagueness called fuzziness, we p...

In many fields, especially in environmetrics and social sciences, it is impossible to obtain exact quantitative data about a variable of interest. Many researchers have suggested that vague, non-precise observations should be described by fuzzy sets. Fuzzy set theory originated by Zadeh (1965) relies on ordering relations that express intensity (degree) of membership of an object in a set. Appl...

Metagraphs are graphical hierarchical structure in which every node is a set having one or more elements. Fuzzy Metagraph and Vague Metagraph are an emerging technique used in the design of many information processing systems like transaction processing systems, Decision Support Systems (DSS), and workflow Systems. In this paper, distinct matrixes have been proposed for Fuzzy Metagraph and Vagu...

This paper presents an integrated fuzzy approach for selecting R&D project. In the integrated approach, fuzzy concepts are used for decision-makers’ subjective judgments to reflect the vague nature of the selection process. Fuzzy ANP and Fuzzy TOPSIS are included in the integrated approach. Fuzzy ANP is used to determine the fuzzy weights of criteria and sub-criteria. Fuzzy TOPSIS aims to rank ...

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This ...

Since much of human reasoning is based on imprecise, vague and subjective values, most of decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Zadeh’s (Zadeh 1965) fuzzy logic has given analysts a tool to represent the human behaviour more precisely, especially where relatively few data exist, and where the expert knowledge about the system is vague and lin...