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Empirical Research in Fuzzy Set Theory

In: Fuzzy Set Theory—and Its Applications

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  • H.-J. Zimmermann

Abstract

The terms model, theory, and law have been used with a variety of meanings, for a number of purposes, and in many different areas of our lives. It is therefore necessary to define more accurately what we mean by models, theories, and laws in order to describe their interrelationships and to indicate their use before we can specify the requirements they have to satisfy and the purposes for which they can be used. To facilitate our task, we shall distinguish between definitions given and used in the scientific area and definitions and interpretations as they can be found in more application oriented areas, which we will call “technologies” in contrast to “scientific disciplines.” By technologies we mean areas such as operations research, decision analysis, and information processing, even though these areas call themselves sometimes theories (i.e., decision theory) and sometimes science (i.e., computer science, management science, etc.). This statement is by no means a value judgment; we only want to indicate that the main goals of these areas are different. While the main purpose of a scientific discipline is to generate knowledge and to come closer to truth without making any value judgments, technologies normally try to generate tools for solving problems better, very often by either accepting or being based on given value schemes. Let us first turn to the area of scientific inquiry and consider the following quotation concerning the definition of the term model: “A possible realization in which all valid sentences of a theory T are satisfied is called a model of T.”

Suggested Citation

  • H.-J. Zimmermann, 2001. "Empirical Research in Fuzzy Set Theory," Springer Books, in: Fuzzy Set Theory—and Its Applications, edition 0, chapter 16, pages 443-475, Springer.
  • Handle: RePEc:spr:sprchp:978-94-010-0646-0_16
    DOI: 10.1007/978-94-010-0646-0_16
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