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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Risk prediction of crime data using ARIMA and LSTM |
| Authors Name: | Shalini M , Aravindarajan V , Swetha E , Vijayalakshmi GM |
| Unique Id: | IJSDR2205046 |
| Published In: | Volume 7 Issue 5, May-2022 |
| Abstract: | 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. |
| Keywords: | crime prediction,Crime data,violence,crime prediction,risk prediction, |
| Cite Article: | "Risk prediction of crime data using ARIMA and LSTM", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 5, page no.244 - 247, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2205046.pdf |
| Downloads: | 000223233 |
| Publication Details: | Published Paper ID: IJSDR2205046 Registration ID:200325 Published In: Volume 7 Issue 5, May-2022 DOI (Digital Object Identifier): Page No: 244 - 247 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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