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RETRACTED ARTICLE: Comparative analysis of time series model and machine testing systems for crime forecasting

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This article was retracted on 14 December 2022

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Abstract

Crime forecasting has been one of the most complex challenges in law enforcement today, especially when an analysis tends to evaluate inferable and expanded crime rates, although a few methodologies for subsequent equivalents have been embraced before. In this work, we use a strategy for a time series model and machine testing systems for crime estimation. The paper centers on determining the quantity of crimes. Considering various experimental analyses, this investigation additionally features results obtained from a neural system that could be a significant alternative to machine learning and ordinary stochastic techniques. In this paper, we applied various techniques to forecast the number of possible crimes in the next 5 years. First, we used the existing machine learning techniques to predict the number of crimes. Second, we proposed two approaches, a modified autoregressive integrated moving average model and a modified artificial neural network model. The prime objective of this work is to compare the applicability of a univariate time series model against that of a variate time series model for crime forecasting. More than two million datasets are trained and tested. After rigorous experimental results and analysis are generated, the paper concludes that using a variate time series model yields better forecasting results than the predicted values from existing techniques. These results show that the proposed method outperforms existing methods.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India

    Sudan Jha

  2. School of Software, Soongsil University, Seoul, 06978, South Korea

    Eunmok Yang

  3. Department of Information Systems, King Abdul Aziz University, Jeddah, Saudi Arabia

    Alaa Omran Almagrabi

  4. Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, UK

    Ali Kashif Bashir

  5. School of Electrical Engineering and Computer Science, NUST, Islamabad, Pakistan

    Ali Kashif Bashir

  6. Department of Computer Science and Engineering, Sejong University, Neungdong-ro, Gwangjin-gu, Seoul, 05006, South Korea

    Gyanendra Prasad Joshi

Authors
  1. Sudan Jha
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  2. Eunmok Yang
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  3. Alaa Omran Almagrabi
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  4. Ali Kashif Bashir
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  5. Gyanendra Prasad Joshi
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Correspondence to Gyanendra Prasad Joshi.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s00521-022-08158-5

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Jha, S., Yang, E., Almagrabi, A.O. et al. RETRACTED ARTICLE: Comparative analysis of time series model and machine testing systems for crime forecasting. Neural Comput & Applic 33, 10621–10636 (2021). https://doi.org/10.1007/s00521-020-04998-1

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  • DOI: https://doi.org/10.1007/s00521-020-04998-1

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