The requirement of user changes according to region wise.
But traditional Expert System contains static rules; hence
these static rules can’t be updated according to user &
region requirement. An enhanced approach namely Rule
Advancement Strategy using Einstein Sum is proposed and
implemented. This approach enables the Expert System’s
inference drawing ability with enhanced intelligence. After
using this approach in expert system the priority of rules
changes according to region and user requirement. A new
algorithm using Rule Advancement Strategy is reported
and implemented in Expert System. The Knowledgebase of
expert system is rich in knowledge. The Knowledgebase
has two types of data. One is static data and second is
dynamic data. Static data can’t be changed but dynamic
data change according to region and user requirement.
Knowledge Base contains the textual as well as pictorial
information of Symptoms and Disease which can help to
better understanding about the Disease and Symptoms. At
last results are compared with existing technique called
Rule Promotion Methodology. The Expert System using
Rule Advancement Strategy is found more intelligent than
the existing technique. The results of this expert system are
also verified by the Domain Expert. Using this technique
an online fuzzy Expert System is implemented using PHP
as front end and MYSQL as back end in horticulture
domain.