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The role of machine learning in drilling operations; a review
Drilling problems such as stick slip vibration/hole cleaning, pipe failures, loss of circulation,
BHA whirl, stuck pipe incidents, excessive torque and drag, low ROP, bit wear, formation …
BHA whirl, stuck pipe incidents, excessive torque and drag, low ROP, bit wear, formation …
Towards an automated decision support system for the identification of additive manufacturing part candidates
As additive manufacturing (AM) continues to mature, an efficient and effective method to
identify parts which are eligible for AM as well as gaining insight on what values it may add …
identify parts which are eligible for AM as well as gaining insight on what values it may add …
Status of data-driven methods and their applications in oil and gas industry
Data-driven methods serve as robust tools to turn data into knowledge. Historical data
generally has not been used in an effective way in analyzing processes due to lack of a well …
generally has not been used in an effective way in analyzing processes due to lack of a well …
The barriers and prospects related to big data analytics implementation in public institutions: A systematic review analysis
Modern society has always relied on data, which is generated by individuals, businesses,
and government entities. This data serves various citizen-centric purposes, including …
and government entities. This data serves various citizen-centric purposes, including …
Enriching analytics models with domain knowledge for smart manufacturing data analysis
H Zhang, U Roy, YTT Lee - International journal of production …, 2020 - Taylor & Francis
Today, data analytics plays an important role in Smart Manufacturing decision making.
Domain knowledge is very important to support the development of analytics models …
Domain knowledge is very important to support the development of analytics models …
Deep understanding in industrial processes by complementing human expertise with interpretable patterns of machine learning
Experts in industrial processes rely on domain knowledge (DK) repositories to identify the
causes of abnormal situations in order to make appropriate decisions that mitigate the …
causes of abnormal situations in order to make appropriate decisions that mitigate the …
Recursive approach to combine expert knowledge and data-driven RSW weldability certification decision making process
Data-driven techniques have shown promising results in the analysis and understanding of
complex welding processes. Data analytics play a significant role to turn data into valuable …
complex welding processes. Data analytics play a significant role to turn data into valuable …
Models, more models, and then a lot more
With increased adoption of Model-Driven Engineering, the number of related artefacts in
use, such as models, metamodels and transformations, greatly increases. To confirm this …
use, such as models, metamodels and transformations, greatly increases. To confirm this …
Preprocessing and Artificial Intelligence for increasing explainability in Mental Health
This paper shows the added value of using the existing specific domain knowledge to
generate new derivated variables to complement a target dataset and the benefits of …
generate new derivated variables to complement a target dataset and the benefits of …
Introduction to model management and analytics
Abstract Model management and analytics (MMA) aims to use models and related artifacts
to derive relevant information to support decision making processes of organizations …
to derive relevant information to support decision making processes of organizations …