The Properties Of Multi Intuitionistic Fuzzy

The support definitions have been extended to fuzzy association rule by making use of t- norm and t-conorm operators as discussed above.\\

Guilford (1967) introduced convergent and divergent thinking as part of a set of five operations that apply in his Structure of Intellect model (SOI model) on six products and four kinds of content, to produce 120 different factors of cognitive abilities. With the SOI model Guilford wanted to give the construct of intelligence a comprehensive model.

There are some major characteristics of formal operational thinking include able to perform mental operations, understanding that 1 stands for object, able to reverse the direction of thought , able to classify objects some characteristic like color, shapes, or size, able to arrange objects along quantitative dimensions such as size or weight, and able to judge objects or quantities that continue to the same even if change in physical appearance (Paul & Jackson,

As stated in our reading there a total of 8 multiple intelligences developed by Howard Gardner. Each type of intelligence is not the same for every person. Everyone has their own unique personality and therefore has their own style of learning or retaining information provided to them. There are certain surveys you can take in order to determine where your particular intelligences fall. I have taken one of these surveys and have chosen three of my top intelligences to explore further and to determine what skills in each type of intelligence are most effective for me to retain new information, not only in my education but

Fuzzy logic is all about the relative importance of precision: use as Fuzzy Logic Toolbox software with MATLAB technical computing software as a tool for solving problems with fuzzy logic. Fuzzy logic is a fascinating area of research because it does a good job of trading off between significance and precision something that humans have been managing for a very long time. In this sense, fuzzy logic is both old and new because, although the modern and methodical science of fuzzy logic is still young, the concept of fuzzy logic relies on age-old skills of human reasoning.

Sensing people are realistic. They focus on the reality of the world by processing information through the five senses. They concentrate on the present moment and find practical solution to difficulties. Intuitive person goes deeper in situation and ideas. They think outside the box and are creative.

Artificial intelligence and machine learning techniques provide a qualitative as well as quantitative assessment of the power system.

Multiple Intelligences (M.I) was a theory Howard Gardner developed in 1983. This is a theory of intelligences were a good way to explain the different ways that people learn. This theory explains how people learn and others learn in different ways. Intelligence is the ability to understand, learn and problem solve or creativity that are valued within one or more cultural settings”. Gardner found that there are eight intelligences and could possibly be more.

Therefore it is one purpose of this paper to explain as simply as possible the core ideas of S-D logic.

Game theorists consider the axiomatization of the utility function in the case of uncertainty a major contribution in von Neumann and Morgenstern. It paved the ground for the modeling of rational decision-making when a decision maker is faced by lotteries. Thereafter a utility function, ui(.), which satisfies the expected utility hypothesis, i.e.

ABSTRACT: Much of the progress in modern logic beyond Aristotle is due to the invention of a precise and powerful formalism, and this is why Haack is reluctant to weaken it. What motivates her to regard deviant and fuzzy logic as extensions rather than rivals of classical logic is its demonstrated capacity for refinement and progress. Thus she sharply distinguishes between a logic dealing with fuzzy concepts (she accepts), and one which is itself fuzzy, i.e., where "true" and "false" cease to be precise concepts (she rejects). While it is often more convenient to retain as much as possible of classical logic because of its simplicity and familiarity, there is nothing in the hermeneutical view of logic to render it

The decision making with multiple criteria (MCDM) has been successfully used in complex business problems. There are several methods for MCDM, such as Analytic Hierarchy process (AHP), Potentially All Pairwise Rankings of All Possible Alternatives (PAPRIKA), Weighted Sum Mode (WSM), Analytic network process (ANP), Multi-Attribute Utility Theory (MAUT) and so forth.

This paper contains the brief introduction of Set theory which included the definition, origination, history and modernization of set theory and mathematical field related to it. The main focus of this paper will be on the application of set theory in different discipline.

Abstract: The quality-based approach SQFE (Suivi Qualite Par le Fournisseur Exterieur) has been introduced by three automotive corporations to measure the quality of supplier products. This approach proposes a general criterion by which inspection samples are classified to different demerit categories with different weights, to compute mean unit demerit for each measurable quality characteristic. However, the assignment of an actual and crisp demerit weight to each sample is unrealistic, in the face of the unavoidable measurement errors as well as the inevitable uncertainty involved in human judgment. In this paper an improved estimation procedure which is based on fuzzy logic instead of bivalent logic, is presented to calculate s. The fuzzy set theory is used to add more accuracy and flexibility to the analysis. For this aim, “likelihood view” has been adapted to generate fuzzy membership function, in order to assign the appropriate demerit weight to each sample. In addition, a numerical example that evaluates products based on the proposed method and compares it with the current standard procedure is presented.

The widely used COA strategy generates the centre of gravity of the possibility distribution of a fuzzy set C .The method gives .