Autoregressive Model for Multivariate Crime Prediction

Yadav, Romika; Sheoran, Savita Kumari

doi:10.1007/978-981-15-3643-4_23

Cited by 3 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yadav and Kumari [15] used autoregressive models and fuzzy membership functions for multivariate crime predictions. They used a dataset from Delhi city in India for the following crimes: vehicular crime, arson, assaults, kidnappings, robberies, theft, and violent assault.…”

Section: State Of the Art Of Crime Forecastingmentioning

confidence: 99%

Short Time Series Forecasting: Recommended Methods and Techniques

et al. 2022

View full text Add to dashboard Cite

This paper tackles the problem of forecasting real-life crime. However, the recollected data only produced thirty-five short-sized crime time series for three urban areas. We present a comparative analysis of four simple and four machine-learning-based ensemble forecasting methods. Additionally, we propose five forecasting techniques that manage the seasonal component of the time series. Furthermore, we used the symmetric mean average percentage error and a Friedman test to compare the performance of the forecasting methods and proposed techniques. The results showed that simple moving average with seasonal removal techniques produce the best performance for these series. It is important to highlight that a high percentage of the time series has no auto-correlation and a high level of symmetry, which is deemed as white noise and, therefore, difficult to forecast.

show abstract

Section: State Of the Art Of Crime Forecastingmentioning

confidence: 99%

Short Time Series Forecasting: Recommended Methods and Techniques

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In addition, there is a challenge to bridge the gap between real‐time necessities and theoretical analysis 16 . So, the developed multivariate crime scene and fuzzy membership is a hybrid technique to predict crime values 17 . Moreover, this technique provides double advantage of crime event‐based multivariate trends and prediction in the virtual environment.…”

Section: Introductionmentioning

confidence: 99%

“…16 So, the developed multivariate crime scene and fuzzy membership is a hybrid technique to predict crime values. 17 Moreover, this technique provides double advantage of crime event-based multivariate trends and prediction in the virtual environment. Also, the accuracy of prediction is capable of statistical approaches.…”

Section: Introductionmentioning

confidence: 99%

Crime activities prediction system in video surveillance by an optimized deep learning framework

Kumar¹,

Reddy²

2022

Concurrency and Computation

View full text Add to dashboard Cite

The video surveillance technology is used to find crime events in public places and capture live public events. Hence, detecting the criminalist before the crime actions is the most needed event to catch the criminalist. However, the presence of noise content in the trained video has raised the difficulties in crime specification by maximizing the complexity range of the data. To overcome this issue, this research has designed a novel lion-based deep belief neural paradigm (LbDBNP) to identify criminals by their activities and handling tools. Initially, three types of datasets were trained to the system then the training flaws were eliminated in the preprocessing layer. Hereafter, the cleaned data is imported to the classification module to detect the crime events present in the video. Subsequently, the designed model is implemented using the Python framework in Windows 10 platform. To evaluate the efficiency of the designed model, the attack is launched in the proposed model after those metrics are calculated. In addition, the robustness of the designed system is verified by three datasets, such as UCSDped1, UCSDped2, and avenue crime. Also, the key parameters of the designed model have been evaluated and compared with other existing schemes to verify the proposed model's robustness by achieving the finest outcomes.

show abstract

Detailed Analysis of Unified Power Flow Controller- A Review

Hanfi¹,

Vishwakarma²

2021

IJOSCIENCE

View full text Add to dashboard Cite

Renewable techniques have become more appealing for producing energy in village and moderately village regions because they reduce degradation of environment and provide a plentiful supply of free and environmental energy. Several research works have been carried out all over the planet to assess and investigate the feasibility of hybrid renewable resources (combination of two or more) with the electricity generation for usage in diverse implementation and livelihoods. An explanation of photovoltaic renewable energy systems is demonstrated in this paper.

show abstract

Autoregressive Model for Multivariate Crime Prediction

Cited by 3 publications

References 9 publications

Short Time Series Forecasting: Recommended Methods and Techniques

Short Time Series Forecasting: Recommended Methods and Techniques

Crime activities prediction system in video surveillance by an optimized deep learning framework

Detailed Analysis of Unified Power Flow Controller- A Review

Contact Info

Product

Resources

About