Mathematical Modeling using Rough Set and Random Forest Model to Predict Wind Speed

• Published in: 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom) pp. 207 - 213
• Main Authors: Das, Ratnakar, Mishra, Jibitesh, Mishra, Sujogya, Pattnaik, P. K., Das, Subhalaxmi
• Format: Conference Proceeding
• Language: English
• Published: Bharati Vidyapeeth, New Delhi 23-03-2022
• Subjects: Chi-Squared Test; Computational modeling; Mathematical models; Meteorological Phenomena; Predictive models; RFM; Rough sets; RST; Soft Computing; Wind speed
• DOI: 10.23919/INDIACom54597.2022.9763275

Prediction of meteorological phenomena using conventional techniques is always a challenge for meteorologists. We developed a novel method for predicting meteorological phenomena by using the Random Forest Model (RFM) and Rough Set Theory (RST). We have used RST to find the most significant meteorological phenomena, and then by using RFM, we have derived a set of predictive results. Using RST on vague meteorological data, we find that the significant meteorological phenomenon is wind speed. After using the RFM based on the outcome, we have predicted the wind speed. We used the Chi-square test to validate our claim. For our analysis, we collected various meteorological data from different parts of our Odisha state in India.