Abstract: Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in advance regarding: ongoing construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. Published papers from year 2013 to 2017 from renowned online search libraries are considered for this research. This review will serve the researchers to analyze the latest work on rainfall prediction with the focus on data mining techniques and also will provide a baseline for future directions and comparisons.

Shabib Aftab, Munir Ahmad, Noureen Hameed, Muhammad Salman Bashir, Iftikhar Ali and Zahid Nawaz, “Rainfall Prediction using Data Mining Techniques: A Systematic Literature Review” International Journal of Advanced Computer Science and Applications(IJACSA), 9(5), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090518

@article{Aftab2018,
title = {Rainfall Prediction using Data Mining Techniques: A Systematic Literature Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090518},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090518},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {5},
author = {Shabib Aftab and Munir Ahmad and Noureen Hameed and Muhammad Salman Bashir and Iftikhar Ali and Zahid Nawaz}
}