This project aims to make correct predictions about an area's risk of coastal inundation with using artificial neural network. People gives information about the area they're in and the artificial intelligence mechanism tells them if they're in danger, or not (based on it's own experiments) For accuracy rate, we've used datas gathered by citizens in our own area. The accuracy rate we've obtained is %95.

This project is solving the Coastal Inundation in Your Community challenge.


In this project, we aimed to make a desicion mechanism which is able to make correct decision's about an area's risk of coastal inundation. As method, we've used artficial intelligence.We've written artficial neural network codes in C++. We've used previous resource's datas for training set. The network has learned the training set.For learning, we've used perceptron algorithm. Process of learning was based on regulation of weights. After reaching ideal weights, we've finished learning. Then, we've obtained a mechanism that can make decisions. People gives information about their area, as inputs. And the mechanism decides based on it's experiments; they are/aren't in danger of floodplain.1 / 0 As test set, we've used datas that gathered by citizens.We've asked the network to guess inputs' label (we've used labeled datas with hidden label). And we've calculated accuracy rate. The accuracy of the tool is %95.

Project Information

License: Academic Free License 3.0 (AFL-3.0)

Source Code/Project URL:



  • Büşra Kılıç
  • Dilara  Bozyılan