Modeling and analysis of crime prediction and prevention

Srivastav, Akhil Kumar; Athithan, S.; Ghosh, Mini

doi:10.1007/s13278-020-00637-8

Cited by 10 publications

(9 citation statements)

References 24 publications

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“… 2018 ; Srivastav et al. 2019 , 2020 ) or entail unidentifiable inverse problems (Lacey and Tsardakas 2016 ), so we are sure that there should be a balance between complexity and applicability. Here is where phenomenological/statistical modeling comes in Lauer et al.…”

Section: Discussionmentioning

confidence: 99%

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Modeling noisy time-series data of crime with stochastic differential equations

Calatayud

Jornet

Mateu

2022

Stoch Environ Res Risk Assess

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We develop and calibrate stochastic continuous models that capture crime dynamics in the city of Valencia, Spain. From the emergency phone, data corresponding to three crime events, aggressions, stealing and women alarms, are available from the year 2010 until 2020. As the resulting time series, with monthly counts, are highly noisy, we decompose them into trend and seasonality parts. The former is modeled by geometric Brownian motions, both uncorrelated and correlated, and the latter is accommodated by randomly perturbed sine-cosine waves. Albeit simple, the models exhibit high ability to simulate the real data and show promising for crimes-interaction identification and short-term predictive policing.

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Section: Discussionmentioning

confidence: 99%

“… 2018 ; Srivastav et al. 2019 , 2020 ). Albeit these theories are powerful to get a deeper understanding of crime patterns, fitting the models to actual crime data is not straightforward and therefore their applicability is lessened.…”

Section: Introductionmentioning

confidence: 99%

Modeling noisy time-series data of crime with stochastic differential equations

Calatayud

Jornet

Mateu

2022

Stoch Environ Res Risk Assess

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“…This theorem is proved using the comparison theorem. Using the same notation as of [18,19] , we re-write the equations for the exposed and infected compartment in (1).…”

Section: Stability Analysismentioning

confidence: 99%

“…For the Numerical simulation of the model, some of the parameter we took from published paper [18,19] and rest of the parameters we have assumed. First we consider the following set of parameters which corresponds to crime-free equilibrium.…”

Section: Numerical Simulationmentioning

confidence: 99%

Modeling Dynamics of the Spread of Crime with Media Impact

Goswami¹,

Athithan

2022

Preprint

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A non-linear mathematical model is developed and analyzed in order to investigate the interactions between the criminal and non-criminal populations while taking into account the influence of media on the non-criminal class. We obtained the basic reproduction number of the model while taking into account constant recruitment and death type demography. The model’s equilibria have been examined , and their stabilities have been thoroughly addressed. The backward bifurcation is presented for basic reproduction number less than one. Sensitivity analysis is conducted on the proposed model to determine the key parameters of basic reproduction number of the model.These model is further expanded to an optimum control problem to investigate the effects of time-dependent crime control rate on the size of the criminal population using Pontryagin’s maximum principle. To demonstrate our analytical findings, we present numerical simulations.

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“…Gonzalez [11] propose a mathematical model of crime by assuming crime as a social epidemic process. The optimal control problem of model of crime is discussed in [6]. A mathematical model of crime that takes into consideration serious and minor criminal activity is discussed in [15].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Model of Armed Criminal Group with Pre-emitive and Repressive Intervention

Nur¹,

Darmawati

2021

Jomta

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Armed Criminal group is one of the problems faced by many countries in the world. Awful behaviour of armed criminal group members can affect a large amount of people. In this paper, we construct a deterministic mathematical model that takes into account persuasive and repressive intervention. We consider crime as a social epidemic. We determine the armed criminal group free equilibrium point and the armed criminal group persistence equilibrium point together with their existence condition. The next generation matrix is used to obtain the basic reproduction number. The local stability conditions of equilibrium points are proved using linearization. We show that the armed criminal group free equilibrium point is globally asymptotically stable under certain condition. Numerical simulations are performed to support our deductive study.

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Modeling and analysis of crime prediction and prevention

Cited by 10 publications

References 24 publications

Modeling noisy time-series data of crime with stochastic differential equations

Modeling noisy time-series data of crime with stochastic differential equations

Modeling Dynamics of the Spread of Crime with Media Impact

Mathematical Model of Armed Criminal Group with Pre-emitive and Repressive Intervention

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