Risk prediction of crime data using ARIMA and LSTM
Shalini M
, Aravindarajan V , Swetha E , Vijayalakshmi GM
crime prediction,Crime data,violence,crime prediction,risk prediction,
Urbanization makes a ton of social issues. One of these issues intrinsic in all urban areas of the world is crime. Police information bases gather a lot of information that could be broke down all together crime percentages. The examination of crime and prediction of number of crime stays quite possibly the most fascinating issue for researchers. For a non-industrial nation like India, it isn't new that individuals know about violations happening regularly. With the quick urbanization of urban areas, we need to continually know about our environmental elements. To keep away from the sad, this work attempt to notice crime percentages by the crossover forecast technique. We proposed a hybrid model based on deep learning methods that incorporates an autoregressive integrated moving average (ARIMA) model and a long short term memory (LSTM) model to work on the precision of crime percentage expectation. Our investigation gives a thorough manual for crime percentage examination of model boundaries with respect to execution in expectation of crime percentage by accuracy calculation from comparing supervise classification machine learning algorithms.
"Risk prediction of crime data using ARIMA and LSTM", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.244 - 247, May-2022, Available :https://ijsdr.org/papers/IJSDR2205046.pdf
Volume 7
Issue 5,
May-2022
Pages : 244 - 247
Paper Reg. ID: IJSDR_200325
Published Paper Id: IJSDR2205046
Downloads: 000347210
Research Area: Computer Science & Technology
Country: Madurai, Tamil Nadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
