AREC Home
About the Department
Research & Publications
Extension
Academics

For more information about this area, please contact:

Russ Tronstad
Extension Economist

Phone: (520) 621-2425
Email: tronstad@ag.arizona.edu

An Example Fuzzy Expert System

For operation of a normal fuzzy expert system only one set of input observations would be necessary. However, to illustrate the fuzzy concepts, lets take an example with 10 observations of energy and protein.

energy = {0., 0., 0., 0., 3.2, 6.1, 10., 3.2, 3.2, 10.}
protein = {0., 3.2, 6.1, 10., 0., 0., 0., 3.1, 3.3, 10.}

The following are the evaluations of theses observations in terms of their membership in the four fuzzy sets we have defined.

• lowenergy = low[energy] {0.993307, 0.993307, 0.993307, 0.993307, 0.858149, 0.24974, 0.00669285, 0.858149, 0.858149, 0.00669285}
  
  
• lowprotein = low[protein] {0.993307, 0.858149, 0.24974, 0.00669285, 0.993307, 0.993307, 0.993307, 0.869892, 0.845535, 0.00669285}
  
  
• highenergy = high[energy] {0.00669285, 0.00669285, 0.00669285, 0.00669285, 0.141851, 0.75026, 0.993307, 0.141851, 0.141851, 0.993307}
  
  
• highprotein = high[protein] {0.00669285, 0.141851, 0.75026, 0.993307, 0.00669285, 0.00669285, 0.00669285, 0.130108, 0.154465, 0.993307}
  

Observation 3 for example has an energy value of 0 and a protein value of 6.1 and the following membership on the energy and protein fuzzy sets.

lowenergy[[3]] = 0.993307
lowprotein[[3]] = 0.24974
highenergy[[3]] = 0.00669285
highprotein[[3]] = 0.75026

Step 1