Prediction of Rainfall Induced Landslides using Machine Learning Algorithms
K.Uma1, C. Ramesh Kumar2, T.R. Saravanan3, M. Basha Khaja4

1K.Uma*, School of Information Technology and Engineering, VIT University, Vellore, India.
2C.Ramesh Kumar, School of Computing Science and Engineering, Galgotias University, Uttar Pradesh, India.
3T.R.Saravanan, Department of CSE, Jeppiaar SRR Engineering college, Chennai.
4M.Basha Khaja, Wipro Technology, Software Engineer, Ireland, United Kingdom.

Manuscript received on November 16, 2019. | Revised Manuscript received on 25 November, 2019. | Manuscript published on December 10, 2019. | PP: 4274-4278 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7725129219/2019©BEIESP | DOI: 10.35940/ijitee.B7725.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Landslide is one of the major natural hazards which is experienced all over the world and causes huge losses to land and property. Most of the landslides are generally caused by multiple factors which act together to destabilize the slope. But among them, the most common trigger for the landslides have been excessive rainfall and no proper planning have been leading to disastrous outcomes. So, in this research, mostly focus on the landslides which are induced due to rainfall to find a solution to the problem. It is present an overview on the challenges being faced in the prediction of Rainfall induced landslides. Also the objective is to find relevant approaches and techniques and judge the best possible method and algorithms which gives the most accurate results.
Keywords: Support Vectors, Probability, Prediction model, Regression, Risk, Accuracy
Scope of the Article: Machine Learning