Predictive models for concrete properties using machine learning and deep learning approaches: A review

MM Moein, A Saradar, K Rahmati… - Journal of Building …, 2023 - Elsevier
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …

Recent advances and application of machine learning in food flavor prediction and regulation

H Ji, D Pu, W Yan, Q Zhang, M Zuo, Y Zhang - Trends in Food Science & …, 2023 - Elsevier
Background Food flavor is a key factor affecting sensory quality. Predicting and regulating
flavor can result in exceptional flavor characteristics and improve consumer preferences and …

Applications of artificial neural networks and machine learning in civil engineering

A Kaveh - Studies in computational intelligence, 2024 - Springer
In today's world, which has witnessed unprecedented advances in technology and computer
science, artificial intelligence has emerged as a top field captivating global attention. Often …

Influence of data splitting on performance of machine learning models in prediction of shear strength of soil

QH Nguyen, HB Ly, LS Ho, N Al-Ansari… - Mathematical …, 2021 - Wiley Online Library
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …

A review on extreme learning machine

J Wang, S Lu, SH Wang, YD Zhang - Multimedia Tools and Applications, 2022 - Springer
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …

Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions

M Aliramezani, CR Koch, M Shahbakhti - Progress in Energy and …, 2022 - Elsevier
A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …

The role of ai, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities

MM Rathore, SA Shah, D Shukla, E Bentafat… - IEEE …, 2021 - ieeexplore.ieee.org
Digital twinning is one of the top ten technology trends in the last couple of years, due to its
high applicability in the industrial sector. The integration of big data analytics and artificial …

Recent advances of chemometric calibration methods in modern spectroscopy: Algorithms, strategy, and related issues

HP Wang, P Chen, JW Dai, D Liu, JY Li, YP Xu… - TrAC Trends in …, 2022 - Elsevier
In recent years, modern spectral analysis techniques, such as ultraviolet–visible (UV-vis)
spectroscopy, mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy, Raman …

Internet of medical things (IoMT)-integrated biosensors for point-of-care testing of infectious diseases

S Jain, M Nehra, R Kumar, N Dilbaghi, TY Hu… - Biosensors and …, 2021 - Elsevier
On global scale, the current situation of pandemic is symptomatic of increased incidences of
contagious diseases caused by pathogens. The faster spread of these diseases, in a …

A systematic literature review on machine learning applications for sustainable agriculture supply chain performance

R Sharma, SS Kamble, A Gunasekaran… - Computers & Operations …, 2020 - Elsevier
Agriculture plays an important role in sustaining all human activities. Major challenges such
as overpopulation, competition for resources poses a threat to the food security of the planet …