Artificial-intelligence-led revolution of construction materials: From molecules to Industry 4.0

XQ Wang, P Chen, CL Chow, D Lau - Matter, 2023 - cell.com
Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …

Effective machine learning model combination based on selective ensemble strategy for time series forecasting

SX Lv, L Peng, H Hu, L Wang - Information Sciences, 2022 - Elsevier
The success of ensemble forecasting heavily depends on the selection and combination of
component models as proven by numerous studies that show the superior performance of …

Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India

RK Paul, M Yeasin, P Kumar, P Kumar… - Plos one, 2022 - journals.plos.org
Background Price forecasting of perishable crop like vegetables has importance
implications to the farmers, traders as well as consumers. Timely and accurate forecast of …

[HTML][HTML] Insights into hot deformation of medium entropy alloys: Softening mechanisms, microstructural evolution, and constitutive modelling—a comprehensive review

SA Kareem, JU Anaele, OF Olanrewaju… - Journal of Materials …, 2024 - Elsevier
The recent discovery of multicomponent principal alloys and the enhanced comprehension
of their physical metallurgy have significantly advanced the understanding of microstructure …

Energy-saving optimization of air-conditioning water system based on data-driven and improved parallel artificial immune system algorithm

S Yang, J Yu, Z Gao, A Zhao - Energy Conversion and Management, 2023 - Elsevier
As the air-conditioning water system is designed according to the maximum load, the system
will deviate from its optimum state while operating under partial load. Therefore, it is critical …

A long-term multivariate time series forecasting network combining series decomposition and convolutional neural networks

X Wang, H Liu, J Du, X Dong, Z Yang - Applied Soft Computing, 2023 - Elsevier
In multivariate time series forecasting tasks, expanding forecast length and improving
forecast efficiency is an urgent need for practical applications. Accurate long-term …

A novel multivariate grey model for forecasting periodic oscillation time series

Y Dang, Y Zhang, J Wang - Expert Systems with Applications, 2023 - Elsevier
To solve the problem that the grey multivariate prediction model cannot well simulate
systems with periodic oscillations, a novel multivariate grey model called the GM (1, N| sin) …

[HTML][HTML] Predictive and correlational analysis of heating energy consumption in four residential apartments with sensitivity analysis using long Short-Term memory and …

MK Kim, B Cremers, N Fu, J Liu - Sustainable Energy Technologies and …, 2024 - Elsevier
The aim of this study is to explore several approaches to analyze how local weather
conditions, indoor CO 2 levels, and façade opening ratios affect the heating energy usage of …

[HTML][HTML] A mathematical framework for improved weight initialization of neural networks using Lagrange multipliers

I de Pater, M Mitici - Neural Networks, 2023 - Elsevier
A good weight initialization is crucial to accelerate the convergence of the weights in a
neural network. However, training a neural network is still time-consuming, despite recent …

Diagnosing Breast Cancer Based on the Adaptive Neuro‐Fuzzy Inference System

S Chidambaram, SS Ganesh, A Karthick… - … Methods in Medicine, 2022 - Wiley Online Library
In this work, a novel hybrid neuro‐fuzzy classifier (HNFC) technique is proposed for
producing more accuracy in input data classification. The inputs are fuzzified using a …