Mathematical tool for predicting the weather condition of coastal regions of Nigeria: A case study of Bayelsa State, Nigeria
Classification of data in its simplicity is a means of categorizing data into different categories according to rules. In this paper, we reviewed some data mining techniques that are relevant to classification of weather data set. Based on the classification and decision tree rules, we generated a different attributes’ table. These attributes were imputed into the WEKA software to produce a decision tree, from which we predicted the appropriate boat users can take based on the weather condition. The results of this study can significantly strengthen decision-making ability of stakeholders who ply the coaster regions of Nigeria, particularly in Bayelsa State. We recommend that bigger boats should be equipped with software that have capabilities for providing artificial intelligence, decision system, sensors, based on weather conditions to facilitate decision-making and also to exhibit intelligence when necessary.
Keywords: Decision tree, Weather, Data Mining, Boat, Water Transportation Sector.