March 15, 2024

Crime Prediction by Comparing Machine Learning and Deep Learning Algorithms

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KMKarenina Nurmelita MalikUniversitas Pembangunan Nasional Veteran Jakarta MPManas PandeyBanaras Hindu University AKAsma KhanGreen University of Bangladesh

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Implication

Literature review compares machine learning and deep learning algorithms for crime prediction, highlighting proactive strategies for urban law enforcement.

Key Points

Comparative evaluation identifies predictive capabilities across multiple models, where deep learning and machine learning forecast future criminal activity patterns.
Literature review contrasts random forest, naive bayes, knn, and svm stacking against an lstm network to evaluate accuracy in mapping historical crime trends.
Predictive modeling through crime prediction algorithms may enable proactive intervention, supporting law enforcement agencies in strategic crime prevention.

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Malik et al. (2024) studied this question.

synapsesocial.com/papers/68e73dd3b6db6435876b7650 https://doi.org/10.1109/icdt61202.2024.10489578

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Implication

Literature review compares machine learning and deep learning algorithms for crime prediction, highlighting proactive strategies for urban law enforcement.

Crime Prediction by Comparing Machine Learning and Deep Learning Algorithms

Discussion

Member takes

Implication

Key Points

Cite This Study

Crime Prediction by Comparing Machine Learning and Deep Learning Algorithms

Discussion

Member takes

Implication

Key Points

Cite This Study

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