An ensemble method combining these individual models was implemented to improve the prediction performance. Through the voting ensemble method, the final \\({R}^{2}\\) score for crime rate prediction was enhanced to 0.8104.Ling, Hneah Guey...
Hence, the proactive prediction of crimes is vital as it empowers law enforcement agencies to make decisions on resource allocation and targeted interventions based on the data, ultimately leading to a more secure and protected community. Additionally, such initiatives raise public awareness, ...
Using Biblioshiny, the top cited documents, publishing journals, influential authors, countries, institutes, and their collaboration have been analyzed. In keyword analysis, it has been explored that Crime prediction and analysis using machine learning is the most advanced topic of research (Roy and ...
Advances in artificial intelligence and machine learning have sparked interest from governments that would like to use these tools for predictive policing to deter crime. However, early efforts at crime prediction have been controversial, because they do not account for systemic biases in police enforce...
We aim at building an alert system for women's safety, using machine learning prediction models. These models will help to achieve a deeper understanding of criminal hotspots. The alert system will function through an Android application that will deliver women alerts if they enter a neighborhood ...
in Tiruchirappalli, Tamil Nadu, India had two main objectives: the prediction of crime using ML models based on emotional data and the identification of future crime hotspots using DL methods applied to crime incident data.
In this scenario Machine Learning can be used to identify the patterns of crimes. The data to feed this Machine Learning approach can be taken from past crime records, social media sentiment analysis, weather data etc. There are five steps in crime prediction by using Machine Learning. Those ...
Crime Prediction Model using Three Classification Techniques: Random Forest, Logistic Regression, and LightGBM Predicting the likelihood of a crime occurring is difficult, but machine learning can be used to develop models that can do so. Random forest, logistic reg... A Alsubayhin,MS Ramzan,B ...
Crime analysis and prediction using machine-learning approach in the case of Hossana Police Commission of machine learning to analyze historical data and the random forest algorithm to classify crimes yields promising results in predicting the type of crime.Be... BZ Wubineh - 《Security Journal》 ...
"Crime Prediction Using Machine Learning (ML)" is a comprehensive project developed in python that employs Machine Learning algorithms. In contemporary yea... C Sambasiva Rao,CH Gayathri,K Gayathri,... - Doctoral Symposium on Computational Intelligence 被引量: 0发表: 2024年 Putting spatial crime...