Abstract
Ground water contamination with Arsenic (As) is one of the foremost issues in the South Asian countries where ground water is one of the foremost sources of drinking water. In Asian countries, especially people of Pakistan living in rural areas are devouring ground water for drinking purpose, and cleaned water is not accessible to them. This arsenic contaminated water is hazardous for human health. The persistence of this study is to study the increasing level of arsenic in ground water in coming years for Khairpur, Sindh Pakistan, which is also increasing the cancer rate (skin cancer, blood cancer) gradually in human body. To predict the arsenic value and cancer risk for the next five years, we have developed two models via Microsoft Azure machine learning with algorithms include Support Vector Machine (SVM), Linear Regression (LR), Bayesian Linear Regression (BLR), Boosted Decision tree (BDT), exponential smoothing ETS, Autoregressive Integrated Moving Average (ARIMA). The developed predictive model named as Arsenic Contamination and Cancer Risk Assessment Prediction Model (ACCRAP model) will help us to forecast the arsenic contamination levels and the cancer rate. The results demonstrated that BLR pose highest prediction accuracy of cancer rate among the four deployed machine learning algorithms.
Highlights
Orthogonal Ground water is one of the major sources of drinking water in the World, in Pakistan
Exponential Smoothing (ETS) and Autoregressive Integrated Moving Average (ARIMA) methods are used for arsenic forecasting for the five-years
Bayesian Linear Regression (BLR), Boosted Decision Tree (BDT), Linear Regression (LR), Support Vector Machine (SVM) machine learning algorithms are deployed for envision of the cancer rate
Summary
Orthogonal Ground water is one of the major sources of drinking water in the World, in Pakistan. Day by day countless changes occur in weather and environment conditions, which influences ground water and indirectly on human health. Ground water contamination due to arsenic became a vital public health issue in Sindh Pakistan [3]. This study predicts the elevated level of arsenic in the coming years for district Khairpur, Sindh Pakistan and the way cancer rate are raised because of arsenic changes in the body. In rural areas of Sindh, arsenic component is gradually developed in the body of the people because of consuming contaminated water and food, and its exposure comes within a variety of skin, blood and scalp cancer [5]. To the best of knowledge this is the foremost attempt towards the forecasting of arsenic for the five years with Exponential Smoothing (ETS) and Autoregressive Integrated Moving Average (ARIMA) methods
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