Expert Systems - Digital Signal Processing in Power System Protection and Control - page 296

Fig. 14.3 An example of
chain of rules

B

C L

M

A K

D

• Identify which rules could be applied,
• Employ a conflict resolution strategy, if needed (the appropriate rules are
selected).

The above issues are explained in more detail in next section.

14.2 Knowledge Processing Methods

The rule-based expert systems contain a number of IF … THEN … rules. The
rules stored in the knowledge base are compared with facts contained in the
database. When the IF (condition) part of the rule matches a fact, the rule is fired
and its THEN (action) part is executed (match-fire procedure). The matching of the
rule IF parts to the facts produces inference chains. The inference chain indicates
how an ES applies the rules to reach a conclusion.
An example of a rule chain is presented in Fig. 14.3 , with the rules defined as
follows:
Rule 1: IF D is true AND L is true THEN M is true
Rule 2: IF B is true AND C is true AND K is true THEN L is true
Rule 3: IF A is true THEN K is true
In case of vast and long-rule chains arriving at the conclusions is not trivial and
may create a lot of technical problems. Examining a vast set of rule chains can be
performed either with so-called forward chaining (data-driven inferencing) or with
backward chaining (goal-driven inferencing) (Fig. 14.4 ). The techniques can be
characterized as follows:

• Forward chaining

- A technique for gathering information and then inferring from it whatever can
be inferred,
- Many rules may be executed that have nothing to do with the established goal,
- If our goal is to infer only one particular fact, the forward chaining inference
technique would not be efficient,
- Any rule can be executed only once,
- The match-fire cycle stops when no further rules can be fired;