International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 10 - Number 1 |
Year of Publication: 2010 |
Authors: S. Maria Wenisch, G.V. Uma, A. Ramachandran |
10.5120/1448-1958 |
S. Maria Wenisch, G.V. Uma, A. Ramachandran . Article:Fuzzy Inference System for an Integrated Knowledge Management System. International Journal of Computer Applications. 10, 1 ( November 2010), 6-10. DOI=10.5120/1448-1958
An integrated and holistic approach to knowledge management system for natural resource management needs to take local indigenous knowledge as one of its components for achieving sustainability. The system of indigenous or local ecological knowledge on natural resource is fuzzy. The integration of such fuzzy knowledge requires a methodology for converting fuzzy data into crisp data for a quantitative analysis. The process of arriving at a conclusion from indigenous knowledge fuzzy data is done using a set of fuzzy inference rules. This work shows that fuzzy inference system is an efficient method to demonstrate defuzzification of the local ecological knowledge using fuzzy inference process. The paper builds a fuzzy inference system from the fuzzy indigenous knowledge system on soil. The inference rules are framed from the fuzzy indigenous knowledge on soil as IF...THEN structures. FIS tool in Matlab is used for building a mamdani fuzzy inference system using the inferences. The relationships between various factors influencing the suitability of soil for crops are produced as the output of the suitability fuzzy inference system.