Abstract
Intense rainfall produces flooding even on dry soil. As heavy rainfall is one of the causes for flooding it is necessary to predict the Rainfall to take necessary precautions for people who are living in risk zone areas. Prediction of Rainfall tomorrow is done accurately using Machine Learning regression and classification Techniques. For Rainfall prediction multiple attributes like Windspeed, Precipitation, Cloudcover, Humidity, Temperature and RainfallToday are considered to predict Rainfall Tomorrow. An ensemble approach is used where predictions from Regression models such as Linear Regression, Polynomial Regression, Ridge Regression and Lasso regression are stacked together and fed as new attributes to Meta Regressor along with Support Vector Regression for making final predictions. Also, predictions from classifications models such as Gaussian Naive Bayes, K-nearest neighbor, Support vector Machine and Random Forest are stacked together and fed as new attributes to Meta Classifier along with Logistic regression which is a binary classifier for higher predictive performance.
Highlights
Flooding is due to continuous water flow towards land that is commonly dry
Algorithm: Input: Rainfall Data set with attributes X= {Windspeed, Precipitation, Cloudcover, Humidity, Temperature, rainfall today} Output: Target Attribute y=RainTomorrow Step1: In first phase classification models Gaussian Naive Bayes, K-nearest neighbor, Support Vector Machine, Random Forest Classification models are trained on X
Different Regression Models are trained on Weather data set to predict the target attribute RainTomorrow in the range of 0 to 1 value
Summary
In case of heavy rainfall for longer durations mostly urban areas are affected with floods due to lack of drainage System. Flash floods are caused to Heavy Rainfall within a short period of time results with harmful and unpredictable destruction. Floods are caused by different reasons, one of the chances for flooding is heavy rainfall. Finding Flood prone areas, identifying the cause of flooding and educating people in nearby areas helps from being affected. Various Machine learning algorithms are used to accurately predict the rainfall in advance based on the atmospheric attributes. If the rainfall is predicted in advance the flood intensity will be reduced by taking necessary precautions.
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