Ads by TechWords

See your link here
Receive the latest technology news and information.
Computerworld Daily News (First Look and Wrap-Up)
Computerworld Blogs Newsletter
The Weekly Top 10
Cloud Computing
View all newsletters




Privacy Policy
 

Sidebar: Seven Truths of Fuzzy Logic

August 30, 2004 12:00 PM ET

Computerworld - 1. Fuzzy logic isn't fuzzy. Fuzzy logic isn't intrinsically imprecise, doesn't violate common sense and produces unambiguous results. "Classical" Boolean logic, in fact, is merely a special case of fuzzy logic.
2. Fuzzy logic is different from probability. With probability, we're trying to determine something about the potential outcome of clearly defined events that may occur at random. With fuzzy logic, we're trying to determine something about the nature of the event itself. Fuzziness is often expressed as ambiguity, not imprecision or uncertainty; it's a characteristic of perception as well as concept.
3. Designing fuzzy sets is easy. Fuzzy sets reflect, in a general way, how people actually think about a problem. It's usually quick and easy to rough out the approximate shape of a fuzzy set. Later on, after some testing or experience, we can adjust its precise characteristics.
4. Fuzzy systems are stable and easily tuned and can be validated. It's faster and easier to create fuzzy sets and build a fuzzy system than it is to create conventional knowledge-based systems, since fuzzy logic handles all the interlocking degrees of freedom. These systems are validated much like conventional systems, but tuning them is usually much simpler.
5. Fuzzy systems aren't neural networks. A fuzzy system attempts to find the intersection, union or complement of the fuzzy control variables. While this is somewhat analogous to both neural networks and linear programming, fuzzy systems approach these problems differently.
6. Fuzzy logic is more than process control. Although some people view fuzzy logic mainly as a tool for process control and signal analysis, that interpretation is too limiting. Fuzzy logic is a way of representing and analyzing information, independent of specific applications.
7. Fuzzy logic is a representational and reasoning process. Fuzzy logic is a powerful and versatile tool for representing imprecise, ambiguous and vague information. It can't solve all problems, but it helps us model difficult, even intractable problems.


Adapted from "The Seven Noble Truths of Fuzzy Logic," by Earl Cox, Computer Design, April 1992

Read more about default in Computerworld's Default Knowledge Center.



Jump to comments

Additional Resources

EFD vs. HDD - What You Need to Know
WHITE PAPER
Enterprise flash drives provide a new Tier 0 storage layer capable of delivering high I/O performance at a very low latency. Proper use of EFDs in an Oracle environment can deliver increased performance compared to fibre channel drives. Read the recommendations for identification of the best DB components for EFDs.
Gartner Research Report: Magic Quadrant for Application Delivery Controllers, 2009
WHITE PAPER
The market for products to improve the delivery of application software over networks remains dynamic and innovative. Vendors focused on solving enterprises' most-pressing application problems have become the top players.
Eight Criteria for Server Load Balancing
WHITE PAPER
Server load balancers are a simple yet highly effective means to scale an application environment while ensuring its availability. Today's solutions should also address application performance and security. Read about the top eight criteria you should consider when choosing a server load balancer and how Citrix NetScaler meets those requirements.

White Papers & Webcasts

The Workday User Experience Video
Watch Workday's Creative Director, Scott Lietzke, discuss the business-centered design philosophy at Workday.

Business Process Framework Demo
Learn about Configurable Business Processes and Calculated Fields. Watch Now!

Manager Experience Demo
Go beyond self-service solutions to perform more effectively. Watch Now.


IT Jobs