مقاله انگلیسی رایگان در مورد کمک به بررسی جرم هوشمند با استفاده از دسته بندی کننده های یادگیری ماشین – IEEE 2021

مقاله انگلیسی رایگان در مورد کمک به بررسی جرم هوشمند با استفاده از دسته بندی کننده های یادگیری ماشین – IEEE 2021

 

مشخصات مقاله
ترجمه عنوان مقاله کمک به بررسی جرم هوشمند با استفاده از دسته بندی کننده های یادگیری ماشین در جرم و اطلاعات قربانی
عنوان انگلیسی مقاله Intelligent Crime Investigation Assistance Using Machine Learning Classifiers on Crime and Victim Information
انتشار مقاله سال ۲۰۲۱
تعداد صفحات مقاله انگلیسی ۴ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
مقاله بیس این مقاله بیس میباشد
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
فرضیه ندارد
مدل مفهومی دارد، تصویر۱ صفحه ۲
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط حقوق، مهندسی کامپیوتر
گرایش های مرتبط حقوق جزا و جرم شناسی، هوش مصنوعی
نوع ارائه مقاله
کنفرانس
مجله / کنفرانس کنفرانس بین المللی درباره کامپیوتر و فناوری اطلاعات- International Conference on Computer and Information Technology
دانشگاه BRAC University, Bangladesh
کلمات کلیدی جرم، تحقیق، سیستم خودکار، دسته بندی، ویژگی ها، برچسب ها
کلمات کلیدی انگلیسی Crime, investigation, Automated system, Classification, Features, Labels
شناسه دیجیتال – doi
https://doi.org/10.1109/ICCIT51783.2020.9392668
کد محصول E16070
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
INTRODUCTION
LITERATURE REVIEW
PROPOSED MODEL
DATASET DETAILS AND PROCESSING
RESULT AND ANALYSIS
CONCLUSION AND FUTURE WORKS
REFERENCES

 

بخشی از متن مقاله:
Abstract
In order to establish peace and justice in a society, it is essential to make proper and correct investigation of crime incidents. With the expansion of the utilization of computerized system to track crime and violence, computer applications can help law enforcement officers in a significant way. In most cases, crime incidents are kept in police database and these can be used for various helpful purpose. In this experiment, we have collected data of crime scenario from Bangladesh Police that had features such as area of crime, type of crime, number of victims and so on. Then we applied machine learning algorithms on the dataset for prediction of some attributes such as criminal age, sex, race, crime method etc. We used four different algorithms for our research: K-Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest Classifier (RFC), Decision Tree Classifier (DTC). Using the aforementioned algorithms with 10 fold cross validation, we achieved different accuracy from all four attribute labels ranging from an average of approximate 75% to an average of approximate 90%. Despite the clear need of further improvement, the results give clear implications that it is possible to achieve well performing automated system for suspect attribute prediction with further work. Finally, we ended the research by comparing and analyzing all the achieved results.
INTRODUCTION
Criminal investigation is a multifaceted problem solving challenge. During investigation, an expert official is often required to examine the location of the crime. The official meticulously examines various important aspects of the crime scene, collects data and eventually analyzes data in order to infer identification information of the criminal. This complicated process of criminal identification demands high critical and reasoning skills. Additionally, most of the time these procedures are needed to be performed fairly quickly since criminals always try to hide all their traces. Therefore, the more time criminals get, the harder it becomes to track him down. In order to address all these complications, the crime scene examiners need to earn lots of experience and analytical skills so that they can make proper use of insightful information. [1] However, very few can earn such interpretative skills which results in a low number of proficient criminal investigators. Therefore, a lack of enough crime investigator is often evident.

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