Universiti Teknologi Malaysia Institutional Repository

A review on applied statistical and artificial intelligence techniques in crime forecasting

Khairuddin, A. R. and Alwee, R. and Haron, H. (2019) A review on applied statistical and artificial intelligence techniques in crime forecasting. In: International Conference on Green Engineering Technology and Applied Computing 2019, IConGETech2 019 and International Conference on Applied Computing 2019, ICAC 2019, 4-5 Feb 2019, Eastin Hotel Makkasan Bangkok, Thailand.


Official URL: https://dx.doi.org/10.1088/1757-899X/551/1/012030


Crime forecasting is an important component of crime analysis towards providing early information about possible crime occurrences in the future. Different models have been proposed to assess different crime data structures and representations. From the literature study conducted, there are several types of crime forecasting models that have been introduced such as statistical model and artificial intelligence (AI) model. Recent trends indicate that researchers have shifted their interest towards AI model due to its flexibility in handling variations in crime data structures. The study found that AI model is capable of capturing nonlinearity pattern of crime data in which statistical model fails to achieve. Moreover, the structure of crime data is mostly nonlinear. Thus, an AI model is favoured among researchers towards developing a robust crime forecasting model. This paper provides a review on the background, trends, and challenges on applied statistical and AI model in crime forecasting.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:artificial intelligence, data structures, forecasting
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:88925
Deposited By: Narimah Nawil
Deposited On:29 Dec 2020 12:43
Last Modified:29 Dec 2020 12:43

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