A review of artificial neural network models for ambient air pollution prediction

SM Cabaneros, JK Calautit, BR Hughes - Environmental Modelling & …, 2019 - Elsevier
Research activity in the field of air pollution forecasting using artificial neural networks
(ANNs) has increased dramatically in recent years. However, the development of ANN …

Predicting resilient modulus of flexible pavement foundation using extreme gradient boosting based optimised models

R Sarkhani Benemaran, M Esmaeili-Falak… - International Journal of …, 2023 - Taylor & Francis
Resilient modulus (MR) plays the most critical role in the evaluation and design of flexible
pavement foundations. MR is utilised as the principal parameter for representing stiffness …

Non-destructive detection of the freshness of air-modified mutton based on near-infrared spectroscopy

P Jin, Y Fu, R Niu, Q Zhang, M Zhang, Z Li, X Zhang - Foods, 2023 - mdpi.com
Monitoring and identifying the freshness levels of meat holds significant importance in the
field of food safety as it directly relates to human dietary safety. Traditional packaging …

“NanoBRIDGES” software: open access tools to perform QSAR and nano-QSAR modeling

P Ambure, RB Aher, A Gajewicz, T Puzyn… - … and Intelligent Laboratory …, 2015 - Elsevier
Nanotechnology is a branch of science and technology that comes with lots of industrial
applications and potential benefits to the society. But the risk associated with the …

Convolutional neural network: Deep learning-based classification of building quality problems

B Zhong, X Xing, P Love, X Wang, H Luo - Advanced Engineering …, 2019 - Elsevier
The rapid development of the construction industry in China has introduced unprecedented
quality-related problems in the country's building industry. In response to this issue, the …

FT-MIR and NIR spectral data fusion: a synergetic strategy for the geographical traceability of Panax notoginseng

Y Li, JY Zhang, YZ Wang - Analytical and bioanalytical chemistry, 2018 - Springer
Three data fusion strategies (low-llevel, mid-llevel, and high-llevel) combined with a
multivariate classification algorithm (random forest, RF) were applied to authenticate the …

Mapping the soil organic matter content in a typical black-soil area using optical data, radar data and environmental covariates

C Luo, W Zhang, X Zhang, H Liu - Soil and Tillage Research, 2024 - Elsevier
Soil organic matter (SOM) plays an extremely important role in soil formation, soil fertility,
environmental protection and the sustainable development of agriculture and forestry …

Geographical origin identification of Chinese red wines using ultraviolet-visible spectroscopy coupled with machine learning techniques

HW Gu, HH Zhou, Y Lv, Q Wu, Y Pan, ZX Peng… - Journal of Food …, 2023 - Elsevier
Identifying geographical origins of red wines produced in specific regions is of great
importance, since the geographical origins of wine influence its quality and price greatly. In …

A building regulation question answering system: A deep learning methodology

B Zhong, W He, Z Huang, PED Love, J Tang… - Advanced Engineering …, 2020 - Elsevier
Regulations play an important role in assuring the quality of a building's construction and
minimizing its adverse environmental impacts. Engineers and the like need to retrieve …

State of the art in the development of adaptive soft sensors based on just-in-time models

A Saptoro - Procedia Chemistry, 2014 - Elsevier
Data-driven soft sensors have gained popularity due to availability of the recorded historical
plant data. The success stories of the implementations of soft sensors, however, involved …