Automatic Anomaly Detection on In-Production Manufacturing Machines Using Statistical Learning Methods

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Environmental Sensor Anomaly Detection Using Learning Machines

Environmental Sensor Anomaly Detection Using Learning Machines

متن کامل

Automatic Anomaly Detection in the Cloud Via Statistical Learning

Performance and high availability have become increasingly important drivers, amongst other drivers, for user retention in the context of web services such as social networks, and web search. Exogenic and/or endogenic factors often give rise to anomalies, making it very challenging to maintain high availability, while also delivering high performance. Given that service-oriented architectures (...

متن کامل

Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods

The problem of anomaly detection has been studied for a long time. In short, anomalies are abnormal or unlikely things. In financial networks, thieves and illegal activities are often anomalous in nature. Members of a network want to detect anomalies as soon as possible to prevent them from harming the network’s community and integrity. Many Machine Learning techniques have been proposed to dea...

متن کامل

Robust Anomaly Detection Using Support Vector Machines

Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RSVMs) was compared with that of conventional support vector machines and nearest neighbor classifiers in separating normal usage profiles from intrusive profiles of computer programs. The results indicate the superiority of RSVMs not only in...

متن کامل

Credit Card Fraud Detection using Data mining and Statistical Methods

Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method using both data mining and statistical tasks, utilizing feature selection, resampling and cost-...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Sensors

سال: 2020

ISSN: 1424-8220

DOI: 10.3390/s20082344