Results 131 to 140 of about 133,406 (290)

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Adaptive feedforward control of closed orbit distortion caused by fast helicity-switching undulators. [PDF]

J Synchrotron Radiat, 2021
Masaki M, Maesaka H, Soutome K, Takano S, Watanabe T, Kubota K, Fujita T, Dewa H, Fukui T, Sugimoto T, Takeuchi M, Tanaka H.   +11 more
europepmc   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Combined Feedback Feedforward Control of a 3-Link Musculoskeletal System Based on the Iterative Training Method. [PDF]

Biomed Res Int, 2021
Valizadeh A, Akbari AA.
europepmc   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

Energy Science &Engineering, EarlyView.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan, Sowmya Ravichandran, Deepak Kumar Sinha, Chandran Ramakrishnan, Omar Almomani   +4 more
wiley   +1 more source

Model-Based Feedforward Control of Part Height in Directed Energy Deposition. [PDF]

Materials (Basel), 2021
Wang Q, Li J, Nassar AR, Reutzel EW, Mitchell WF.   +4 more
europepmc   +1 more source

A Hybrid EV Charging Architecture Integrating DC Fast Charging and Wireless Power Transfer

Energy Science &Engineering, EarlyView.
A hybrid EV charging architecture combining DC fast charging and wireless power transfer is proposed. The system achieves high efficiency, grid compliance, and reliable bidirectional operation, offering a scalable solution that enhances user convenience while paving the way for smarter, future‐ready EV charging infrastructure.
Ali Almaktoof, Mohamad Taha, Marco Adonis, Kareem Halablab   +3 more
wiley   +1 more source

Two Aspects of Feedforward Control During a Fencing Lunge: Early and Anticipatory Postural Adjustments. [PDF]

Front Hum Neurosci, 2021
Akbaş A, Marszałek W, Bacik B, Juras G.   +3 more
europepmc   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source