Fuzzy Logic Applied to Inflation Control in the Nigerian Economy

Ibrahim Goni; Mohammed Alhaji Maunde Usman; Auwal Nata’ala

doi:doi:10.11648/j.mlr.20180304.11

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Fuzzy Logic Applied to Inflation Control in the Nigerian Economy

Ibrahim Goni, Mohammed Alhaji Maunde Usman, Auwal Nata’ala

Published in Machine Learning Research (Volume 3, Issue 4)

Received: 9 March 2019 Accepted: 22 April 2019 Published: 23 May 2019

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Abstract

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.

Published in	Machine Learning Research (Volume 3, Issue 4)
DOI	10.11648/j.mlr.20180304.11
Page(s)	69-72
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Fuzzy Logic, Inflation, Defuzzification, Fuzzification, Knowledge Base, Mamdani

References

[1]	Victor OA. The Causes of Persistent Inflation in Nigeria. CBN Journal of Applied Statistics, 2016; 7 (2).
[2]	Eskey 10 causes of inflation in Nigeria, Information guide in Nigeria, 2018 available online at https: //infoguidenigeria.com/causes-inflation-nigeria/
[3]	Marcus F. (2011). The Application of Fuzzy Logic in Determining Linguistic Rules and Associative Membership Functions for the Control of a Manufacturing Process, M. Engr. Dissertation Dublin Institute of Technology India.
[4]	Ponce-Cruz, FD. Ramirez-Figueroa. Intelligent Control Systems with LabVIEW™ Springer 2010.
[5]	Kalaichelvi A, Malini, PH, Application of fuzzy soft sets to investment decision making problem, International Journal of Mathematical Sciences and Applications 2011; 1(3), 1583-1586.
[6]	Karaca F. Taş, V. Decision making problem for life and non-life insurances, Journal of BAUN Inst. Sci. Technol. 2018; 20 (1), 572-588.
[7]	Özgür NY., Taş N., A note on "application of fuzzy soft sets to investment decision making problem", Journal of New Theory, 2015; 7 1-10.
[8]	Taş, N., Özgür NY., Demir, P. An application of soft set and fuzzy soft set theories to stock management, Süleyman Demirel University Journal of Natural and Applied Sciences 2017; 21 (2), 791-196.
[9]	Vincenzo D. G., Pierfrancesco D. P. and Giovanni B. C. (2017) Valuation of Real Estate Investments through. Fuzzy Logic. Buildings MDPI.
[10]	Jagendra D. and Ramesh T. (2015) Design of Mamdani - Type Model for Predicting the Future Price of Fuel on theBasis of Demand and Supply International Journal on Recent and Innovation Trends in Computing and Communication 3 (6). 3667-3671.

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APA Style

Ibrahim Goni, Mohammed Alhaji Maunde Usman, Auwal Nata’ala. (2019). Fuzzy Logic Applied to Inflation Control in the Nigerian Economy. Machine Learning Research, 3(4), 69-72. https://doi.org/10.11648/j.mlr.20180304.11

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ACS Style

Ibrahim Goni; Mohammed Alhaji Maunde Usman; Auwal Nata’ala. Fuzzy Logic Applied to Inflation Control in the Nigerian Economy. Mach. Learn. Res. 2019, 3(4), 69-72. doi: 10.11648/j.mlr.20180304.11

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AMA Style

Ibrahim Goni, Mohammed Alhaji Maunde Usman, Auwal Nata’ala. Fuzzy Logic Applied to Inflation Control in the Nigerian Economy. Mach Learn Res. 2019;3(4):69-72. doi: 10.11648/j.mlr.20180304.11

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@article{10.11648/j.mlr.20180304.11,
  author = {Ibrahim Goni and Mohammed Alhaji Maunde Usman and Auwal Nata’ala},
  title = {Fuzzy Logic Applied to Inflation Control in the Nigerian Economy},
  journal = {Machine Learning Research},
  volume = {3},
  number = {4},
  pages = {69-72},
  doi = {10.11648/j.mlr.20180304.11},
  url = {https://doi.org/10.11648/j.mlr.20180304.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20180304.11},
  abstract = {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.},
 year = {2019}
}

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TY  - JOUR
T1  - Fuzzy Logic Applied to Inflation Control in the Nigerian Economy
AU  - Ibrahim Goni
AU  - Mohammed Alhaji Maunde Usman
AU  - Auwal Nata’ala
Y1  - 2019/05/23
PY  - 2019
N1  - https://doi.org/10.11648/j.mlr.20180304.11
DO  - 10.11648/j.mlr.20180304.11
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 69
EP  - 72
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20180304.11
AB  - 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.
VL  - 3
IS  - 4
ER  -

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Author Information

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

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Plain Text BibTeX RIS

APA Style

Ibrahim Goni, Mohammed Alhaji Maunde Usman, Auwal Nata’ala. (2019). Fuzzy Logic Applied to Inflation Control in the Nigerian Economy. Machine Learning Research, 3(4), 69-72. https://doi.org/10.11648/j.mlr.20180304.11

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ACS Style

Ibrahim Goni; Mohammed Alhaji Maunde Usman; Auwal Nata’ala. Fuzzy Logic Applied to Inflation Control in the Nigerian Economy. Mach. Learn. Res. 2019, 3(4), 69-72. doi: 10.11648/j.mlr.20180304.11

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AMA Style

Ibrahim Goni, Mohammed Alhaji Maunde Usman, Auwal Nata’ala. Fuzzy Logic Applied to Inflation Control in the Nigerian Economy. Mach Learn Res. 2019;3(4):69-72. doi: 10.11648/j.mlr.20180304.11

Copy | Download

@article{10.11648/j.mlr.20180304.11,
  author = {Ibrahim Goni and Mohammed Alhaji Maunde Usman and Auwal Nata’ala},
  title = {Fuzzy Logic Applied to Inflation Control in the Nigerian Economy},
  journal = {Machine Learning Research},
  volume = {3},
  number = {4},
  pages = {69-72},
  doi = {10.11648/j.mlr.20180304.11},
  url = {https://doi.org/10.11648/j.mlr.20180304.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20180304.11},
  abstract = {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.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Fuzzy Logic Applied to Inflation Control in the Nigerian Economy
AU  - Ibrahim Goni
AU  - Mohammed Alhaji Maunde Usman
AU  - Auwal Nata’ala
Y1  - 2019/05/23
PY  - 2019
N1  - https://doi.org/10.11648/j.mlr.20180304.11
DO  - 10.11648/j.mlr.20180304.11
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 69
EP  - 72
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20180304.11
AB  - 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.
VL  - 3
IS  - 4
ER  -

Copy | Download