• Anjana Ravi

Big data analysis is an approach for identifying and analyzing patterns and trends. And the unknown relationship between the data. It is often a complex process of analyzing a large volume of various data. The use of deep learning techniques in big data analytics is to optimize the data and to analyze the data more precisely. The data visualization shows different facts about the crime data. In this paper, we construct two deep learning models, LSTM and Stacked LSTM. And we predict the crime type using these models. The models are compared using the accuracy performance of crime prediction. The result shows that the Stacked LSTM is better in prediction accuracy than the LSTM. And this comparison can be used for finding a better model. The experimental results using these models can be used for making decisions in police departments and law enforcement organizations.

Deep learning, LSTM, Stacked LSTM, Data visualization, Time series forecasting

"Crime Prediction and Analysis using Big Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.b576-b586, July-2021, Available :http://www.jetir.org/papers/JETIR2107201.pdf

"Crime Prediction and Analysis using Big Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppb576-b586, July-2021, Available at : http://www.jetir.org/papers/JETIR2107201.pdf