Write a summary of the abstract below

ABSTRACT: 

Floods cause a lot of damage, especially in developing countries, and so flood predictions are some of the best candidates for improvement by artificial intelligence. Because countries on the coasts are under particular pressure to prevent or otherwise mitigate flood damage wherever possible, people have turned to artificial intelligence - specifically, machine learning. Machine learning models can attempt to predict flooding using numerical, physical, data-driven, and statistical techniques. Some of these models work better when implemented as hybrids of different techniques. This paper will explore some of the effective methods of predicting floods using ML systems.

Floods are very common and devastating natural disasters which have the potential to take and ruin lives. An article from Abunyewah, Maund, Okyere, and Gajendran (2020) states that out of the total number of natural disasters that occurred in the sub-Saharan between 2000 and 2019, 64% of them were flood cases (Abunyewah, Maund, Okyere, Gajendran, 2020).

With the damage flood brings and how common it is in the sub Saharan region of Africa, it is not surprising for us to see it's effects in Ghana. That is why we are striving to make an artificial intelligence(AI) computer system which can make predictions for the probability of flood occurring over a certain period of time by taking into consideration various factors such as quality of drainage system, urban planning, and many others