Application of Hidden Markov Model in Yam Yield Forecasting.
No Thumbnail Available
Date
2022-06-06
Journal Title
Journal ISSN
Volume Title
Publisher
African Journal Online (AJOL), Soutrh Africa
Abstract
Providing the government and farmers with reliable and dependable information about crop yields
before each growing season begins is the thrust of this research. A four-state stochastic model was
formulated using the principle of Markov, each state of the model has three possible observations.
The model is designed to make a forecast of yam yield in the next and subsequent growing seasons
given the yam yield in the present growing season. The parameters of the model were estimated from
the yam yield data of Niger state, Nigeria for the period of sixteen years(2001-2016). After which,
the model was trained using Baum-Welch algorithm to attend maximum likelihood. A short time
validity test conduct on the model showed good performance. Both the validity test and the future
forecast shows prevalence of High yam yield, this attest to the reality on the ground, that Niger State
is one of the largest producers of yam in Nigeria. The general performance of the model, showed that
it is reliable therefore, the results from the model could serve as a guide to the yam farmers and the
government to plan strategies for high yam production in the region.
Description
A journal publication
Keywords
Citation
Lawal Adamu, Saidu Daudu Yakubu, Didigwu Ndidiamaka Edith, Abdullahi Abubakar & Khadeejah James Audu and Isaac Adaji. (2022). Application of Hidden Markov Model in Yam Yield Forecasting. Scientia Africana, 21(2), 39-52.