A Novel Approach to Predicting the Risk of Illegal Activity and Evaluating Law Enforcement Using WideDeep SGRU Model
- Title
- A Novel Approach to Predicting the Risk of Illegal Activity and Evaluating Law Enforcement Using WideDeep SGRU Model
- Creator
- Mishra P.; Anusha P.; Kumar A.; Pal S.; Patra J.P.; Chauhan A.
- Description
- The main reaction to the illicit extraction of natural resources in protected areas around the world is law enforcement patrols headed by rangers. On the other hand, research on patrols' efficacy in reducing criminal behavior is lacking. Similarly, tactics to enhance the effectiveness of patrol organization and monitoring have received very little attention. Sequencing is crucial for model training, feature selection, and preprocessing. Preprocessing steps include cleaning, discretizing, duplicating, and normalizing data. Feature selection makes use of genetic algorithms, which are basically search algorithms with an evolutionary bent that factor in natural selection and genetics. Training stacked GRU models necessitates meticulous feature management. Even the most cutting-edge algorithms, GRU and BiGRU, are no match for the suggested technique. An astounding 97.24% accuracy grade was disclosed by the results, showcasing exceptional growth. 2024 IEEE.
- Source
- 1st International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Gated Recurrent Unit(GRU); Illegal Activity; Law Enforcement Officers (LEO)
- Coverage
- Mishra P., Computer Science and Application Reva University, Karnataka, Bangalore, India; Anusha P., R.M.K. Engineering College, Department of ECE, Tamilnadu, Kavaraipettai, India; Kumar A., SCA Manav Rachna International Institute of Research and Studies, Haryana, Faridabad, India; Pal S., Computer Science and Engineering Indian Institute of Technology Jammu, Jammu & Kashmir (UT), Jagti, India; Patra J.P., EE And EEE Krupajal Engineering College-KEC, Odisha, Puri, India; Chauhan A., CHRIST (Deemed to be University), Department of Life sciences School of Sciences, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835037180-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Mishra P.; Anusha P.; Kumar A.; Pal S.; Patra J.P.; Chauhan A., “A Novel Approach to Predicting the Risk of Illegal Activity and Evaluating Law Enforcement Using WideDeep SGRU Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19346.