A review on the modelling of carbonation of hardened and fresh cement-based materials

X You, X Hu, P He, J Liu, C Shi - Cement and Concrete Composites, 2022 - Elsevier
Different models have been proposed to investigate and predict the carbonation process of
cement-based materials. This paper firstly introduces the carbonation process occurred in …

Piecewise linear neural networks and deep learning

Q Tao, L Li, X Huang, X Xi, S Wang… - Nature Reviews Methods …, 2022 - nature.com
As a powerful modelling method, piecewise linear neural networks (PWLNNs) have proven
successful in various fields, most recently in deep learning. To apply PWLNN methods, both …

Machine learning prediction of specific capacitance in biomass derived carbon materials: Effects of activation and biochar characteristics

X Yang, C Yuan, S He, D Jiang, B Cao, S Wang - Fuel, 2023 - Elsevier
The preparation process of biomass-based biochar materials is usually screened using
traditional trial-and-error experiments. In this approach, the electrochemical properties of …

A machine learning model for predicting composition of catalytic coprocessing products from molecular beam mass spectra

MA Jabed, Y Kim, C Yarbrough… - ACS Sustainable …, 2023 - ACS Publications
Demand for the development of an automated and integrated refining process for biofuels
has increased in recent years due to the lack of generalized process inspection tools. In bio …

Silas: A high-performance machine learning foundation for logical reasoning and verification

H Bride, CH Cai, J Dong, JS Dong, Z Hóu… - Expert Systems with …, 2021 - Elsevier
This paper introduces a new high-performance machine learning tool named Silas, which is
built to provide a more transparent, dependable and efficient data analytics service. We …

Machine learning models for estimating above ground biomass of fast growing trees

W Wongchai, T Onsree, N Sukkam… - Expert Systems with …, 2022 - Elsevier
Biomass is a renewable and sustainable energy resource that can potentially be substituted
for fossil fuels, which have a negative impact on the environment including the production of …

Energy Supply Control of Wireless Powered Piecewise Linear Neural Network

C Hou, Q Huang - IEEE Transactions on Automation Science …, 2023 - ieeexplore.ieee.org
Piecewise linear neural network (PLNN) possesses universal approximation ability for
continuous functions on the compact domain, and for a PLNN in which the hidden neuron …

Forecasting 24 h averaged PM concentration in the Aburrá Valley using tree-based machine learning models, global forecasts, and satellite information

JS Pérez-Carrasquilla, PA Montoya… - Advances in …, 2023 - ascmo.copernicus.org
We develop a framework to forecast 24 h averaged particulate matter (PM 2.5)
concentrations 4 d in advance in ground-based stations over the metropolitan area of the …

Piecewise linear trees as surrogate models for system design and planning under high-frequency temporal variability

Y Wu, CT Maravelias - European Journal of Operational Research, 2024 - Elsevier
The design and planning of systems subject to high-frequency time-varying conditions (eg,
prices, resource supplies, and customer demand) requires the solution of multi-period …

Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B1 Concentration Classification in Single Maize Kernels

Q Zhou, W Huang, X Tian - Agriculture, 2022 - mdpi.com
Aflatoxin B1 (AFB1) is a very strong carcinogen, maize kernels are easily infected by this
toxin during storage. Rapid and accurate identification of AFB1 is of great significance to …