Fuzzy Logic

Fuzzy Logic: A Practical Approach focuses on the processes and approaches involved in fuzzy logic, including fuzzy sets, numbers, and decisions. The book first elaborates on fuzzy numbers and logic, fuzzy systems on the job, and Fuzzy Knowledge Builder. Discussions focus on formatting the knowledge base for an inference engine, personnel detection system, using a knowledge base in an inference engine, fuzzy business systems, industrial fuzzy systems, fuzzy sets and numbers, and quantifying word-based rules. The text then elaborates on designing a fuzzy decision and Fuzzy Thought Amplifier for complex situations. Topics include origins of cognitive maps, Fuzzy Thought Amplifier, training a map to predict the future, introducing the Fuzzy Decision Maker, and merging interests. The publication takes a look at fuzzy associative memory, fuzzy sets as hypercube points, and disk files and descriptions, including Fuzzy Thought Amplifier, Fuzzy Decision Maker, and composing and creating a memory. The text is a valuable source of data for researchers interested in fuzzy logic.

Foreword

Chapter 1. The Fuzzy World

Apples, Oranges, Or In Between?

Is There Life Beyond Math?

Vague Is Better

Discovering Fuzziness

The Uses Of Fuzzy Logic

Fuzzy Control Systems

Other Commercial Fuzzy Systems

The Value Of Fuzzy Systems

Advantages and Disadvantages

Fuzzy Decision-Making

Fuzziness And Asian Nations

Fuzzy Systems And Uncertainty

Probability and Bayesian Methods

Nonprobabilistic Methods

Fuzzy Systems And Neural Networks

Chapter 2. Fuzzy Numbers And Logic

Fuzzy Numbers

Meet FuzNum Calc

Performing Fuzzy Arithmetic

Behind the Scenes With FuzNum Calc

Fuzzy Sets

Set Theory

Touring UniCalc

Multielement Sets

Union, Intersection, and Implication

Difference

Complement

Crisp And Fuzzy Logic

Rules of Inference

Logical Statements

As-Then And As-Do Rules—A Sneak Preview

Quantifying Word-Based Rules

Chapter 3. Fuzzy Systems on the Job

Fuzzy Tools

Fuzzy Knowledge Builder™ for a Fuzzy Expert System

Fuzzy Decision-Maker™

Fuzzy Thought Amplifier™

Fuzzy Systems

Creating A Fuzzy Control System

Identify and Name Fuzzy Inputs

Identify and Name Fuzzy Output

Create the Fuzzy Membership Functions

Construct the Rule Base

Decide How to Execute the Actions

Fuzzy Business Systems

Industrial Fuzzy Systems

Fuzzy-Neuro Sewage Pumping Station

Fuzzy Insulin Infusion System For Diabetics

Fuzzy Consumer Products

Chapter 4. Fuzzy Knowledge Builder™

Knowledge Builder's Design

Program Organization

Program File Structure

Lunar Lander

Lunar Lander's Vertical Axis

Lunar Lander's Horizontal Axis

Printing Your Graphics Displays

Personnel Detection System

Naming and Defining the Dimensions and Sets

Improving the Matrix's Operation

Formatting The Knowledge Base For An Inference Engine

Using A Knowledge Base In An Inference Engine

Chapter 5. Designing a Fuzzy Decision

The Decision Process

Introducing The Fuzzy Decision Maker™

Deciding Which College To Attend

Naming Your Goals

Name Your Constraints

Name Your Alternatives

Rank the Importances of Your Goals and Constraints

How Well Do the Alternatives Satisfy the Goals?

Regional Transportation System

Goals

Constraints

Alternatives

Importances

Satisfactions

The Decision Process

Merging Interests

The Scenario

The Alternatives

The Goals

The Constraints

George's Version

Martha's Version

Comparing the Two Versions

Inside The Fuzzy Decision Maker

Importances

Satisfactions

The Decision

Chapter 6. Fuzzy Thought Amplifier™ for Complex Situations

Dynamic Complexities In Everyday Life

Origins Of Cognitive Maps

Crisp Cognitive Maps

Fuzzy Cognitive Maps

Fuzzy Thought Amplifier™

Normal Operation

"Trained" Operation

Simple Fuzzy Thought Amplifiers™

Stable Map

Oscillation

Chaos

Catplant

Naming and Defining the States

Creating Events

Event Values and Names

Adding Dynamic Graphics

Running Cycles

Adding Bias

Running Cycles with the Added Bias

Adding Additional States

Running the Augmented CatPlant

Health Care System

The States

The Events

Running the Healthcare Map Cycles

Importance of the Healthcare Map

Training A Map To Predict The Future

The Scenario

The States

The Events

Training the Map

Predicting the Future

How The Fuzzy Thought Amplifier™ Works

Definition Method

Incremental Method

Training Function

Concluding Thoughts

Appendix A. Fuzzy Associative Memory (FAM)

FAMCALC

Composing A Memory

Creating A Memory

How FamCalc Works

Step 1

Step 2

Appendix B. Fuzzy Sets as Hypercube Points

Sets As Points

Using Koskocalc

Interaction Of A Set And Its Complement

Far Crisp And Near Crisp

Measuring A Set's Size

Interaction Of Two Fuzzy Sets

Distance

Subsethood

Appendix C. Disk Files and Descriptions

Library Files

Dr. Fuzzy's Calculators

Fuzzy Knowledge Builder™ Files

Example Knowledge Base

Example Inference Engines

Example Problems

Fuzzy Decision Maker™

Choosing a College

Legal Problem

Unemployment

Financial Planning

Changing Residence

Fuzzy Thought Amplifier™

Readme File

Appendix D. Inference Engine Programs

QuickBasic Simple Inference Engine

QuickBasic Fast Inference Engine

C Language Inference Engine

Fuzz-C Inference Engine

Motorola 68HC05 Assembly Simple Inference Engine

Appendix E. Other Fuzzy Architecture

Flops

How FLOPS Works

Badger—An Animal Guessing Game

Parallel FLOPS

State Machines

Crisp State Machine

Fuzzy State Machine

Putting a Fuzzy State Machine Into Operation

The Rules and the Inference Method

Bibliography

Articles

Books

Conference Proceedings

Index