Volume 3, Issue 4, December 2018, Page: 69-72
Fuzzy Logic Applied to Inflation Control in the Nigerian Economy
Ibrahim Goni, Department Computer Science, Faculty of Science, Adamawa State University, Mubi, Nigeria
Mohammed Alhaji Maunde Usman, Department of Economics, Faculty of Social and Management Science, Adamawa State University, Mubi, Nigeria
Auwal Nata’ala, Department of Computer Science, School of Information Technology Federal Polytechnic, Kaura Namoda, Zamfara State, Nigeria
Received: Mar. 9, 2019;       Accepted: Apr. 22, 2019;       Published: May 23, 2019
DOI: 10.11648/j.mlr.20180304.11      View  890      Downloads  82
In this research work, a fuzzy logic system for inflation control in Nigerian economy is presented. The system consists of four (4) major components which include; the Knowledge base, the Fuzzification, the Inference engine and Defuzzification. Knowledge base were developed based on the discussion with the domain expert and observations of the Nigerian economy. Mamdani's fuzzy inference engine were used to infer data from the rules developed. This resulted in the establishment of some degrees of membership functions of input variables on the output. The methodology allows for High, Low, Yes and No to be applied in order to get the required result. Gaussian membership function was employed to evaluate the degree of participation of each input parameter and the defuzzification technique used in this work is Centriod of Area. Fuzzy logic system has been developed as an alternative to the traditional methods, in order to control inflation in the Nigerian economy.
Fuzzy Logic, Inflation, Defuzzification, Fuzzification, Knowledge Base, Mamdani
To cite this article
Ibrahim Goni, Mohammed Alhaji Maunde Usman, Auwal Nata’ala, Fuzzy Logic Applied to Inflation Control in the Nigerian Economy, Machine Learning Research. Vol. 3, No. 4, 2018, pp. 69-72. doi: 10.11648/j.mlr.20180304.11
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