Reliable Real‐Time Seismic Signal/Noise Discrimination With Machine Learning
نویسندگان
چکیده
منابع مشابه
Reliable Classifications with Machine Learning
In the past decades Machine Learning algorithms have been successfully used in several classification problems. While they often significantly outperform domain experts (in terms of classification accuracy or otherwise), they are mostly not being used in practice. A plausible reason for this is that it is difficult to obtain an unbiased estimation of a single classification’s reliability. While...
متن کاملRealtime Encrypted Traffic Identification using Machine Learning
Accurate network traffic identification plays important roles in many areas such as traffic engineering, QoS and intrusion detection etc. The emergence of many new encrypted applications which use dynamic port numbers and masquerading techniques causes the most challenging problem in network traffic identification field. One of the challenging issues for existing traffic identification methods ...
متن کاملMaking Reliable Diagnoses with Machine Learning: A Case Study
In the past decades Machine Learning tools have been successfully used in several medical diagnostic problems. While they often significantly outperform expert physicians (in terms of diagnostic accuracy, sensitivity, and specificity), they are mostly not used in practice. One reason for this is that it is difficult to obtain an unbiased estimation of diagnose’s reliability. We propose a genera...
متن کاملMachine Repair Queueing System with with Non-Reliable Service Stations And Heterogeneous Service Discipline (RESEARCH NOTE)
This investigation deals with M/M/R/N machine repair problem with R non-reliable service stations which are subjected to unpredictable breakdown. 1here is provision of an additional server to reduce backlog in the case of heavy load of failed machines. 1he permanent service stations repair the failed machines at an identical rate m and switch to faster repair rate when all service stations are ...
متن کاملMachine-learning Based Automated Fault Detection in Seismic Traces
The Initial stages of velocity model building (VMB) start off from smooth models that capture geological assumptions of the subsurface region under analysis. Acceptable velocity models result from successive iterations of human intervention (interpreter) and seismic data processing within complex workflows. The interpreters ensure that any additions or corrections made by seismic processing are...
متن کاملذخیره 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: Journal of Geophysical Research: Solid Earth
سال: 2019
ISSN: 2169-9313,2169-9356
DOI: 10.1029/2018jb016661