@article{SisLab1838,
          volume = {453},
          author = {Hai Chau Nguyen and Thi Ngoc Anh Le},
       booktitle = {Advanced Computational Methods for Knowledge Engineering},
           title = {Using Local Weather and Geographical Information to Predict Cholera Outbreaks in Hanoi, Vietnam},
       publisher = {Springer},
            year = {2016},
         journal = {Advanced Computational Methods for Knowledge Engineering Volume 453 of the series Advances in Intelligent Systems and Computing},
             doi = {doi:10.1007/978-3-319-38884-7\_15},
           pages = {195--212},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1838/},
        abstract = {In 2007, repeated outbreaks of cholera in Hanoi have raised
the need to have up-to-date evidence on the impact of factors on cholera epidemic, which is essential for developing an early warning system. We have successfully built models to predict cholera outbreaks in Hanoi from
2001 to 2012 using Random Forests method. We found that geographical factors - the number of cholera cases of a district of interest and its neighbours - are very important to predict accurately cholera cases besides the weather factors. Among weather factors, temperature and
relative humidity are the most important. We also found that
prediction accuracy of our models, measured in adjusted coefficient of determination, will decrease by 0.0076 if prediction length increases by one day.}
}