Hidden Markov Model and Its Application in Rainfall Pattern Prediction

Knowing the nature of rainfall distribution before each growing season begins in most parts of the world, especially in developing countries has always been a fundamental problem to the farmers, and this has over the years led to improper crop planning and cultivation, consequently led to poor harvest. This book demonstrates the application of Hidden Markov Model (HMM) in rainfall pattern prediction for the purpose of crop production using empirical data. The validity tests for the models showed that they are reliable and dependable. Therefore, results from these models could serve as a guide to the farmers and the government to plan strategies for high crop production in the region. The results from the models could also assist the residents to better understand the dynamics of rainfall which may be helpful for effective planning and viable crop production.

Autorentext

Dr. Lawal Adamu is from Fiche-Kuchi, Paiko, Niger State, Nigeria. He has First Degree in Mathematics and Computer Science, Masters Degree in Mathematics and PhD Degree in Applied Mathematics. He is a Lecturer with Department of Mathematics Federal University of Technology, Minna, Nigeria. His Research Area is Optimization Theory.