Article-Journal

Proxy quality control of biomass particles using thermogravimetric analysis and Gaussian process regression models
The temperature experienced by reactants during preparation in a reactor is a key component in determining the yield and homogeneity of …
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Real-time process operation evaluation and model reliability assessment for chemi-thermomechanical pulping process
In this paper, a real-time chemi-thermomechanical pulping (CTMP) process was investigated, where opportunities were explored to …
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Simultaneous digital twin identification and signal-noise decomposition through modified generalized sparse identification of nonlinear dynamics
A digital twin provides a digital replication of a physical system for remote monitoring, viewing, and control objectives. It has the …
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Predicting and Optimizing Syngas Production from Fluidized Bed Biomass Gasifiers: A Machine Learning Approach
Biomass gasification is one of the primary thermal conversion processes where fluidized bed reactors are often used to produce syngas …
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An efficient improved African vultures optimization algorithm with dimension learning hunting for traveling salesman and large-scale optimization applications
Exploring the finest shortest-path traveling salesman optimization application is a typical NP-hard problem. Similarly the solution of …
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Using stochastic programming to train neural network approximation of nonlinear MPC laws
To facilitate the real-time implementation of nonlinear model predictive control (NMPC), this paper proposes a deep learning-based NMPC …
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High-performance and parallel computing techniques review: Applications, challenges and potentials to support net-zero transition of future grids
The transition towards net-zero emissions is inevitable for humanity’s future. Of all the sectors, electrical energy systems emit the …
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Predicting xylose yield from prehydrolysis of hardwoods: A machine learning approach
Hemicelluloses are amorphous polymers of sugar molecules that make up a major fraction of lignocellulosic biomasses. They have …
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Causal discovery based on observational data and process knowledge in industrial processes
Causal discovery approaches are gaining popularity in industrial processes. Existing causal discovery algorithms can indeed find some …
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An Improved Load Forecasting Method Based on the Transfer Learning Structure under Cyber-Threat Condition
Smart grid is regarded as an evolutionary regime of existing power grids. It integrates artificial intelligence and communication …
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