Machine learning applications in power system fault diagnosis: Research advancements and perspectives
Newer generation sources and loads are posing new challenges to the conventional power
system protection schemes. Adaptive and intelligent protection methodology, based on …
system protection schemes. Adaptive and intelligent protection methodology, based on …
Understanding big data analytics for manufacturing processes: insights from literature review and multiple case studies
Today, we are undoubtedly in the era of data. Big Data Analytics (BDA) is no longer a
perspective for all level of the organization. This is of special interest in the manufacturing …
perspective for all level of the organization. This is of special interest in the manufacturing …
An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system
H Liang, J Zou, K Zuo, MJ Khan - Mechanical Systems and Signal …, 2020 - Elsevier
The throttle valve is the core equipment to managed pressure drilling (MPD) technology. PID
controller is the most widely used throttle valve control algorithm. However, in the wellhead …
controller is the most widely used throttle valve control algorithm. However, in the wellhead …
The linear random forest algorithm and its advantages in machine learning assisted logging regression modeling
Direct measurements of formation properties such as the shale volume, porosity,
permeability, and fluid saturation are often accompanied by expensive cost and are time …
permeability, and fluid saturation are often accompanied by expensive cost and are time …
A strategic roadmap for the manufacturing industry to implement industry 4.0
J Butt - Designs, 2020 - mdpi.com
Industry 4.0 (also referred to as digitization of manufacturing) is characterized by cyber
physical systems, automation, and data exchange. It is no longer a future trend and is being …
physical systems, automation, and data exchange. It is no longer a future trend and is being …
Industrial metaverse towards Industry 5.0: Connotation, architecture, enablers, and challenges
The development of any industry cannot be done without social expectations. The industrial
metaverse arises from customers' emphasis on their value, their desire for immersive …
metaverse arises from customers' emphasis on their value, their desire for immersive …
Mapping forest fire susceptibility using spatially explicit ensemble models based on the locally weighted learning algorithm
Fire is among the most dangerous and devastating natural hazards in forest ecosystems
around the world. The development of computational ensemble models for improving the …
around the world. The development of computational ensemble models for improving the …
Computational machine learning approach for flood susceptibility assessment integrated with remote sensing and GIS techniques from Jeddah, Saudi Arabia
Floods, one of the most common natural hazards globally, are challenging to anticipate and
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …
estimate accurately. This study aims to demonstrate the predictive ability of four ensemble …
Prediction of coalbed methane production based on deep learning
Z Guo, J Zhao, Z You, Y Li, S Zhang, Y Chen - Energy, 2021 - Elsevier
Coalbed methane (CBM) is a clean energy source. The prediction of CBM production is a
critical step during CBM exploitation and utilization, especially for geological well selection …
critical step during CBM exploitation and utilization, especially for geological well selection …
Evaluation and development of a predictive model for geophysical well log data analysis and reservoir characterization: Machine learning applications to lithology …
This work critically evaluated the applicability of machine learning methodology applied to
automated well log creation towards reliable lithology prediction and subsequent reservoir …
automated well log creation towards reliable lithology prediction and subsequent reservoir …