[HTML][HTML] Potential of artificial intelligence-based techniques for rainfall forecasting in Thailand: A comprehensive review

M Waqas, UW Humphries, A Wangwongchai… - Water, 2023 - mdpi.com
Rainfall forecasting is one of the most challenging factors of weather forecasting all over the
planet. Due to climate change, Thailand has experienced extreme weather events, including …

[HTML][HTML] Rainfall prediction system using machine learning fusion for smart cities

A Rahman, S Abbas, M Gollapalli, R Ahmed, S Aftab… - Sensors, 2022 - mdpi.com
Precipitation in any form—such as rain, snow, and hail—can affect day-to-day outdoor
activities. Rainfall prediction is one of the challenging tasks in weather forecasting process …

Rainfall prediction using machine learning & deep learning techniques

CZ Basha, N Bhavana, P Bhavya… - … on electronics and …, 2020 - ieeexplore.ieee.org
In India, Agriculture is the key point for survival. For agriculture, rainfall is most important.
These days rainfall prediction has become a major problem. Prediction of rainfall gives …

A SVR–ANN combined model based on ensemble EMD for rainfall prediction

Y Xiang, L Gou, L He, S Xia, W Wang - Applied Soft Computing, 2018 - Elsevier
Accurate and timely rainfall prediction is very important in hydrological modeling. Various
prediction methods have been proposed in recent years. In this work, information regarding …

Analysing brain networks in population neuroscience: a case for the Bayesian philosophy

D Bzdok, DL Floris… - … Transactions of the …, 2020 - royalsocietypublishing.org
Network connectivity fingerprints are among today's best choices to obtain a faithful
sampling of an individual's brain and cognition. Widely available MRI scanners can provide …

[PDF][PDF] Comparative analysis of data mining techniques for Malaysian rainfall prediction

S Zainudin, DS Jasim, AA Bakar - Int. J. Adv. Sci. Eng. Inf. Technol, 2016 - researchgate.net
Climate change prediction analyses the behaviours of weather for a specific time. Rainfall
forecasting is a climate change task where specific features such as humidity and wind will …

Crop production-ensemble machine learning model for prediction

N Balakrishnan… - International Journal of …, 2016 - search.proquest.com
Data Mining is the most believable approach of the present digital world for analyzing mass
of data sets to obtain unnoticed relationship. The method used for the analysis of statistical …

[PDF][PDF] Rainfall prediction in Lahore City using data mining techniques

MA Shabib Aftab, N Hameed, MS Bashir… - International journal of …, 2018 - academia.edu
Rainfall prediction has extreme significance in countless aspects and scopes. It can be very
helpful to reduce the effects of sudden and extreme rainfall by taking effective security …

A comparative study of classification algorithms for forecasting rainfall

D Gupta, U Ghose - 2015 4th International Conference on …, 2015 - ieeexplore.ieee.org
India is an agricultural country which largely depends on monsoon for irrigation purpose. A
large amount of water is consumed for industrial production, crop yield and domestic use …

[HTML][HTML] Deep learning-based univariate prediction of daily rainfall: application to a flood-prone, data-deficient country

IV Necesito, D Kim, YH Bae, K Kim, S Kim, HS Kim - Atmosphere, 2023 - mdpi.com
There are several attempts to model rainfall time series which have been explored by
members of the hydrological research communities. Rainfall, being one of the defining …