TABLE OF CONTENTS This chapter serves to review the basic principles and descriptions of neural networks and fuzzy logic. As a result of studying this chapter, the student should be able to:
Describe the basic principles of fuzzy logic
Describe the acronyms and basic terminology as used in neural networking and fuzzy logic applications.
In the real world there is a lot of vague and imprecise conditions that defy a simple true or False statement as a description of their state. The computer and its binary logic are incapable of adequately representing these vague, yet understandable, states and conditions. Fuzzy logic is a branch of machine intelligence that helps computers understand the variations that occur in an uncertain and very vague world in which we exist.
Fuzzy logic manipulates such vague concepts as warm or going fast , in such a manner that it helps us to design things like air conditioners and speed control systems to move or switch from one set of control criteria to another, even when the reason to do so is because It is too warm, or not warm enough to go faster or slow down a bit : all of these instructions make sense to us, but are far removed from the digital world of just binary 1s and 0s.
The true and false statements that are absolute in there meaning come from a defined starting location and are designed to terminate at a...
