Machine learning predictive modeling of the price of cassava derivative (GARRI) in the South West Of Nigeria

• Autorzy: Olanloye O. , Oduntan E.

Identyfikatory

DOI

doi:10.23743/acs-2018-05

• Języki publikacji: EN

Abstrakty

EN

Fluctuation in prices of Agricultural products is inevitable in developing countries faced with economic depression and this, has brought a lot of inadequacies in the preparation of Government financial budget. Consumers and producers are poorly affected because they cannot take appropriate decision at the right time. In this study, Machine Learning(ML) predictive modeling is being implemented using the MATLAB Toolbox to predict the price of cassava derivatives (garri) in the South Western part of Nigeria. The model predicted that by the year 2020, all things being equal, the price of (1kg) of garri will be 500. This will boost the Agricultural sector and the economy of the nation.

Słowa kluczowe

EN

fluctuation; prices; machine learning; predictive model; cassava derivative

PL

fluktuacja; cena; nauczanie maszynowe; model predykcyjny; pochodna manioku

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2018
• Tom: Vol. 14, no 1
• Strony: 53--63
• Opis fizyczny: Bibliogr. 16 poz., fig., tab.

Twórcy

autor

Olanloye O.

• Department of Computer Science, Emmanuel Alayande College of Education, Oyo

autor

Oduntan E.

• Department of Computer Science, Federal Polytechnic, Ilaro

Bibliografia

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