Читать книгу Introduction to Fuzzy Logic - James K. Peckol - Страница 73

1 1.1 In the chapter opening, we introduced the term learning. Describe what it means.

2 1.2 Identify the three laws of thought and briefly describe each of them.

3 1.3 The chapter identified what is termed Feigenbaum's five‐phase learning process. Identify and describe each of those phases.

4 1.4 Based on Feigenbaum's learning process, identify and describe each member of the corresponding six‐level taxonomy.

5 1.5 In the context of this chapter, discuss what the term fuzzy means.

6 1.6 Identify and describe the difference between a classical set and a fuzzy set.

7 1.7 What is a fuzzy membership function? What information does such a function give you?

8 1.8 Formulate and graph a membership function for the concept very tall.

9 1.9 Formulate and graph membership functions for Example s 1.2 and 1.3.

10 1.10 What kind of information are we expressing with a crisp membership graph? What kind of information does such a graph give you?

11 1.11 What kind of information are we expressing with a fuzzy membership graph? What kind of information does such a graph give you?

12 1.12 Why do you think that membership graphs have different shapes?

13 1.13 Identify and describe how crisp and fuzzy membership graphs differ.

14 1.14 The chapter identified two kinds of imprecision. What are they and describe each and the differences.

15 1.15 To effectively design modern real‐world systems, the chapters identified several important things. Identify and describe them.

16 1.16 Draw and annotate a membership graph for members of the crisp set old people.

17 1.17 Draw and annotate a membership graph for members of the fuzzy set old people.