Signal Model for the Prediction of Wind Speed In Nigeria



Rapid development of wind energy as an alternative source of power is providing rich environment for wind energy related research. Several mathematical models have been used to study wind data and the models are mainly physical and statistical models. In this study, a signal

Modeling approach is developed to predict wind speed data in Nigeria. The signal modeling approach is based on the Markov property, which implies that given the present wind speed state, the future of the system is independent of its past. A Markov process is in a sense the probabilistic analog of causality and can be specified by defining the conditional distribution of the random process.

Key words: wind speed, dynamical system, signal model, Markov chain, ergodicity.

Full Text: PDF
Download the IISTE publication guideline!

To list your conference here. Please contact the administrator of this platform.

Paper submission email:

ISSN (Paper)2224-3232 ISSN (Online)2225-0573

Please add our address "" into your email contact list.

This journal follows ISO 9001 management standard and licensed under a Creative Commons Attribution 3.0 License.

Copyright ©