IEEE Machine Learning Projects 2025 2026 - Crime Hotspot Prediction using Machine Learning - IEEE Machine Learning Projects for Final Year

Crime Hotspot Prediction using Machine Learning - IEEE Machine Learning Projects for Final Year To get this project Visit Website: http://www.ieeexpert.com/ Email: [email protected] ABSTRACT Crime prediction is of great significance to the formulation of policing strategies and the implementation of crime prevention and control. Machine learning is the current mainstream prediction method. However, few studies have systematically compared different machine learning methods for crime prediction. This paper takes the historical data of public property crime from 2015 to 2018 from a section of a large coastal city in the southeast of China as research data to assess the predictive power between several machine learning algorithms. Results based on the historical crime data alone suggest that the LSTM model outperformed KNN, random forest, support vector machine, naive Bayes, and convolutional neural networks. In addition, the built environment data of points of interests (POIs) and urban road network density are input into LSTM model as covariates. It is found that the model with built environment covariates has better prediction effect compared with the original model that is based on historical crime data alone. Therefore, future crime prediction should take advantage of both historical crime data and covariates associated with criminological theories. Not all machine learning algorithms are equally effective in crime prediction. LSTM LSTM is a kind of deep neural network based on RNN. The core of LSTM is to add a special unit (memory module) to learn the current information and to extract the related information and rules between the data, so as to transfer the information. LSTM is more suitable for deep neural network calculation because of memory module to slow down information loss. Each memory module has three gates, including input gate (it), forget gate (ft), and output gate (ot). They are used to selectively memorize the correction parameters of the feedback error function as the gradient decreases. More Projects - https://bit.ly/495LVbb Contact us on - +91 9363932473 Ieee Xpert, India. The Best Bulk Service Provider for IEEE Solutions Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support #crimeprediction #machinelearningprojects #finalyearprojects Comparison of machine learning algorithms for predicting crime hotspots, using machine learning algorithms to analyze crime data, crime prediction using machine learning project, Crime prediction using machine learning project, Crime prediction and analysis using Machine learning ppt, FBI crime data using Machine learning with data analysis ppt