Forecasting the Trends and Patterns of Crime in Bangladesh using Machine Learning Model

Biswas, Al Amin; Basak, Sarnali

doi:10.1109/icct46177.2019.8969031

Cited by 20 publications

(10 citation statements)

References 11 publications

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“…Many studies have explored the domain of crime management, suggesting various methods employing machine learning algorithms for forecasting. Highlighting the crucial role of characteristic choice and data origins, a huge part of this investigation has been centered in nations with elevated crime rates like India, Bangladesh [10,11,12,13], Brazil [14], and Colombia [15], with specific attention on urban areas. Curiously, regions in Asian countries like China display decreased crime rates, molding the outlook of its inhabitants [16].…”

Section: Related Workmentioning

confidence: 99%

Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts

Escobedo,

Tapia,

Gutierrez

et al. 2024

IJACSA

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Crime continues to be an issue, in Metropolitan Lima, Peru affecting society. Our focus is on property crimes. We recognized the lack of studies on predicting these crimes. To tackle this problem, we used regression techniques such as XGBoost, Extra Tree, Support Vector, Bagging, Random Forest and AdaBoost. Through GridsearchCV we optimized hyperparameters to enhance our research findings. The results showed that Extra Tree Regression stood out as the model with an R2 value of 0.79. Additionally, error metrics like MSE (185.43) RMSE (13.62) and MAE (10.47) were considered to evaluate the model's performance. Our approach considers time patterns in crime incidents. Contributes, to addressing the issue of insecurity in a meaningful way.

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Section: Related Workmentioning

confidence: 99%

Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts

Escobedo,

Tapia,

Gutierrez

et al. 2024

IJACSA

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“…The more the value of this metric is, we consider the more precise the predictive model to be. Equation 4shows how R-squared is calculated [21].…”

Section: Evaluation Metricsmentioning

confidence: 99%

Analysis of heavy metal contents in some commercial turmeric samples available at Dhaka, Bangladesh

Rahman

Akter

et al. 2021

Jahangirnagar Univ. J. Biol. Sci.

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Nowadays, the use of spices and other herbs have extensively increased due to their medicinal values all over the world. However, the monitoring of heavy metal contamination in spices has also been increased in recent years. A study has been conducted to determine the concentration of eight heavy metals such as Lead (Pb), Cadmium (Cd), Chromium (Cr), Arsenic (As), Zinc (Zn), Iron (Fe), Copper (Cu) and Manganese (Mn) in mainly three different types of turmeric samples (Curcuma longa). The turmeric samples analyzed were (i) Unpacked bulk powder available at three different local markets in Dhaka (ii) Packed and marketed by three branded companies, and (iii) Raw turmeric directly collected from different local farmlands. The samples were analyzed using Atomic Absorption Spectroscopy (AAS). The concentration of most of the heavy metals were found within the limit recommended by WHO (6.0000 ppm) except lead (12.3469 ppm) in unpacked-3 bulk sample. This study also showed the concentration of heavy metals were present in a lower amount in packed power samples compared to unpacked bulk powder samples. The result of this analysis would be helpful for public awareness in consumption of different spices. The concerned authorities who are responsible for monitoring and regulating the food chain in the market in our country may also get a great message about heavy metal contamination of spices. Jahangirnagar University J. Biol. Sci. 9(1 & 2): 13-20, 2020 (June & December)

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“…Crime is a form of social subjugation that is detrimental to the well-being of the general population (Biswas & Basak, 2019). Crime is a significant issue in numerous developing nations (Khatun & Islam, 2018;Sharif & Uddin, 2021).…”

Section: Introductionmentioning

confidence: 99%

Nature of Crime and Challenges of Policing in Haor Areas of Bangladesh: A Study in Kishoreganj and Netrokona Districts

Miah,

Shaulin

2024

IJQR

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Green criminology is a multidisciplinary field that seeks to explain the relationship between crime and geography. Bangladeshi criminologists and crime preventionists are increasingly conscious of crime-location relationships. This study aims to explore with a new eye the lifestyle of the people of haor areas to find out the root causes of crimes and the challenges of policing in haors areas as well. This study is conducted based on the qualitative approach. The study employed an in-depth interview strategy and focus group discussions (FGDs) to gather information. The findings of the study reveal that the main causes for crime in hoar areas include economic insolvency, lack of education, detached communication system, lack of steady employment, lack of adequate land survey, and pedigree contention within families. The result also shows that the police of hoar areas face difficulties in performing their duties due to poor communication, lack of manpower, political influence, inadequate logistics, and modern weapons. It is essential to study this topic to identify the relationship between geography and crime, which will help to control the crime rate in hoar areas through an effective and modern policing system.

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Forecasting the Trends and Patterns of Crime in Bangladesh using Machine Learning Model

Cited by 20 publications

References 11 publications

Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts

Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts

Analysis of heavy metal contents in some commercial turmeric samples available at Dhaka, Bangladesh

Nature of Crime and Challenges of Policing in Haor Areas of Bangladesh: A Study in Kishoreganj and Netrokona Districts

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