Automation and Computational Intelligence for Road Maintenance and Management

4Fuzzy and Its Recent Advances

4.1 Introduction

As mentioned in Chapter 1, there are different types of road surface failures that can be visually analyzed and interpreted. The use of image processing tools generates data for analysis, which in many cases, and requires the use of fuzzy methods to remove ambiguity or quantification. This chapter introduces the concepts of various fuzzy sets that will be required in the following Chapters 6, 7, and 8. Type‐2 and ‐3 fuzzy sets as well as their operations will be discussed in Sections 4.1.2 and 4.1.6. Since research on fuzzy set theory only emerged recently within the last 50 years, a thorough understanding is still lacking. Therefore, this book provides a summary of the basic concepts and operations that are applicable to the study of Type‐1, ‐2, and new on ‐3 fuzzy sets.

We also summarize the definition of fuzzy variables and explain how this linguistic is to be used in various fuzzy rules, as a powerful method for modeling nonquantitative ambiguous descriptive and computable quantitative parameters. In infrastructure management, especially road paving, we encounter many descriptive issues, including the severity and extent of damages. The description of this type of failure is usually inaccurate, vague, and unclear. As such, these indicators themselves are ambiguous and descriptive (low, medium, and high). Quantitative modulation of these types of nonnumerical parameters requires special quantified methods. In fact, in the real ...