Non-Destructive Spectroscopic and Imaging Techniques for the Detection of Processed Meat Fraud
نویسندگان
چکیده
منابع مشابه
the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance
با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
Application of Morphological Method for Detection of Unauthorized Tissues in Processed Meat Products
Background: Nowadays, there is an increase of meat and animal carcass consumption worldwide. Due to the economic value of meat, the likelihood of using unauthorized tissue is possible in meat products. Based on these observations, the aim of the present study was to apply morphological method for detection of unauthorized tissues in processed meat products. Methods: In this study, a to...
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15 صفحه اولData Mining Techniques for Fraud Detection
The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision tree-based algorithm and rule-based algorithm. We present Bayesian classification model to detect ...
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Due to the dramatic increase of fraud which results in loss of billions of dollars worldwide each year, several modern techniques in detecting fraud are continually evolved and applied to many business fields. Fraud detection involves monitoring the behaviour of populations of users in order to estimate, detect, or avoid undesirable behaviour. Undesirable behaviour is a broad term including mis...
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ژورنال
عنوان ژورنال: Foods
سال: 2021
ISSN: 2304-8158
DOI: 10.3390/foods10020448