BUILDING FUZZY EXPERT SYSTEMS
William Siler, PhD
E-Mail: wsiler@aol.com
This page has been referenced 
times.
You may download the self-extracting file <>manual.exe (229,882 bytes)
Your comments, positive and (especially desired) negative will be most
appreciated. Email to:
William Siler
CONTENTS
Chapter 1: Fuzzy Mathematics: Fuzzy Logic, Fuzzy Sets, Fuzzy Numbers.
1.1 Fuzzy Logic.
1.2 Fuzzy Sets.
1.3 Fuzzy Numbers.
Chapter 1 Questions.
Chapter 2: Defining Your System: Purpose, Conclusions to be Reached, Data.
2.1: An Overview.
2.2: Structuring the solution: overall purpose, specific conclusions, data.
2.2.1: Overall purpose.
2.2.2 Possible conclusions.
2.2.3 Data.
2.2.4 Reviewing your scheme.
2.3 Mapping out the reasoning process.
2.4 Blocking out the solution.
Chapter 2 Questions
Chapter 3: Rule-Based Reasoning: Antecedent and Consequent.
3.1 Rules: a Formalism for Thought Processes.
3.2 Sample Rules from a Diagnostic Expert System.
3.3 Handling Uncertainties in Data.
Chapter 3 Questions
Chapter 4: Data-Driven Rules: When is a Rule Fireable?
4.1 When Is a Rule Activated?
4.2 Thresholds and Rule Fireability.
Chapter 4 Questions
Chapter 5: Reasoning Patterns and Rule-Firing Schemes.
5.1 Deductive reasoning and serial rule firing.
5.2 Inductive reasoning and parallel rule firing.
5.3 Summary.
Chapter 5 Questions
Chapter 6: Fuzzy Sets: Using Descriptive Words in Reasoning.
6.1 What is a fuzzy set?
6.2 Ambiguities and Contradictions.
Chapter 6 Questions
Chapter 7: Fuzzifying: Using Descriptive Words instead of Numbers.
7.1 Membership Functions and Fuzzification.
7.2 Using fuzzy sets to represent numbers in an expert system.
Chapter 7 Questions
Chapter 8: Defuzzifying: Converting Fuzzy Set Confidences into Numbers.
8.1 What Is Defuzzification?
8.2 How Do We Defuzzify a Fuzzy Set?
8.3 What Defuzzification Options Are Available?
Chapter 8 Questions
Chapter 9: Fuzzy Numbers and Approximate Comparisons.
9.1 Fuzzy Numbers: Uncertain Values.
9.2 Comparing Fuzzy Numbers.
9.3 Hedges - crudely 25, roughly 25, about 25, nearly 25.
Chapter 9 Questions
10.1 Fuzzy Logic.
10.2 Rule-based reasoning.
10.2.1 Rule structure.
10.2.2 Confidences and rules.
10.2.3 Firing a rule: inference engines and memory modification.
10.3 Fuzzy sets.
10.4 Fuzzifying numbers into fuzzy sets.
10.5 Defuzzifying fuzzy sets into numbers.
Chapter 10 Questions
Chapter 11 Decision strategies: serial rule firing.
11.1 General description of serial rule firing.
11.2 Depth-first search of a decision tree.
11.3 Economizing on number of rules: placing expert knowledge in a data base rather than in rules.
11.4 General characteristics of serial rule firing.
Chapter 11 Questions
Chapter 12 Decision strategies: parallel rule firing.
12.1 General description of parallel rule firing.
12.2 Structure of psychiatric screening program.
12.3 Structure of echocardiogram image analysis programs.
Chapter 12 Questions
Chapter 13: Simple Time Series Analysis.
13.1: An Overview.
13.2 Moving Averages.
13.3 Using time lags.
13.3.1 Detecting baselines and baseline shift.
13.3.2 Detecting high-frequency noise.
13.4 Summary.
Chapter 13 Questions
Chapter 14: Working On-Line in Real Time.
14.1 What is different about real-time on-line work?
14.2 On-line data input and output hardware.
14.3 Memory storage requirements: how to avoid filling up memory.
14.4 Response time requirements: how fast can we process data with FLOPS?
14.5 Processing algorithms.