Prediction of Accident Severity Using Artificial Neural Network: A Comparison of Analytical Capabilities between Python and R

Imran Chowdhury Dipto, A. F. M. Moshiur Rahman, Tanzila Islam, H. Rahman
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Abstract

Large amount of data has been generated by Organizations. Different Analytical Tools are being used to handle such kind of data by Data Scientists. There are many tools available for Data processing, Visualisations, Predictive Analytics and so on. It is important to select a suitable Analytic Tool or Programming Language to carry out the tasks. In this research, two of the most commonly used Programming Languages have been compared and contrasted which are Python and R. To carry out the experiment two data sets have been collected from Kaggle and combined into a single Dataset. This study visualizes the data to generate some useful insights and prepare data for training on Artificial Neural Network by using Python and R language. The scope of this paper is to compare the analytical capabilities of Python and R. An Artificial Neural Network with Multilayer Perceptron has been implemented to predict the severity of accidents. Furthermore, the results have been used to compare and tried to point out which programming language is better for data visualization, data processing, Predictive Analytics, etc.
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用人工神经网络预测事故严重程度:Python和R分析能力的比较
组织产生了大量的数据。数据科学家正在使用不同的分析工具来处理这类数据。有许多工具可用于数据处理、可视化、预测分析等。选择合适的分析工具或编程语言来执行任务是很重要的。在本研究中,对Python和r这两种最常用的编程语言进行了比较和对比。为了进行实验,我们从Kaggle收集了两个数据集,并将其合并为一个数据集。本研究通过使用Python和R语言对数据进行可视化处理,生成一些有用的见解,并为人工神经网络的训练准备数据。本文的范围是比较Python和r的分析能力。实现了一个带有多层感知器的人工神经网络来预测事故的严重程度。此外,结果被用来比较,并试图指出哪种编程语言更适合数据可视化,数据处理,预测分析等。
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