Developing Recursive Forward Chaining Method in Ternary Grid Expert Systems

The performance of expert systems is determined by the performance of it main components. One of mentioned component is inference engine. It inferences the knowledge of expert system and gives answer to user. Since the idea of ternary grid issued in 2004, there is only several developed method, technique or engine working on ternary grid knowledge model. In 2010 an inference method of expert system based on ternary grid was developed. The process of inference implements iterative forward chaining. The disadvantage of mentioned method is low efficiency because of the high number of iterative process. In order to improve the efficiency, a new method of forward chaining in ternary grid has been developed. It implements recursive process. This paper describes the development of inference engine of expert system that can work in ternary grid knowledge model. The strategy to inference knowledge uses forward chaining with recursive process. The design result is implemented in the form of software. The result of experiment shows that the inference process works properly and more efficient in comparison to the previous developed iterative forward chaining.