We are into the process of developing expert system for evaluation of motivational strategies on human resources.
The expert systems are those, which mimic human expert level in a very narrow and domain which requires specialized knowledge. The most popular type of expert system is rule based expert system. But the applicability of rule base system is questionable when it is very hard to derive complete set of rules. Another popular type of expert system is fuzzy expert system. But every variable cannot be assigned value in fuzzy boundaries. Each type of expert system has its own strengths and weaknesses. If we combine the two approaches then we can get the advantages of both and might be able to eliminate the disadvantages up to certain extent. The combinations of the two technologies are called hybrid system.
1. Deriving rules for development of rule base expert system to evaluate motivational strategies on human resources is not possible, as human’s preference and perception for motivation keep changing.
1. From the analysis of literature review, we concluded that ANN proves to the best technique when traditional technique is not able to solve the problem.
2. Hence we decide to explore the option where we can combine ANN with rule base expert system, and it leads us to explore the concept of hybrid neural expert system further.
In the second phase of the paper, we are exploring the concept of hybrid neural expert system for evaluating motivational strategies on human resources.