Time series prediction of tunnel boring machine (TBM) performance during excavation using causal explainable artificial intelligence (CX-AI)

K Wang, L Zhang, X Fu - Automation In Construction, 2023 - Elsevier
Since early warning is significant to ensure high-quality tunneling boring machine (TBM)
construction, a real-time prediction method based on TBM data is proposed. To solve the …

Predicting municipal solid waste gasification using machine learning: A step toward sustainable regional planning

Y Yang, H Shahbeik, A Shafizadeh, S Rafiee, A Hafezi… - Energy, 2023 - Elsevier
The gasification process can treat and valorize municipal solid waste (MSW) in an
environmentally and economically friendly way. Using this process, MSW can be safely …

Performance prognosis of FRCM-to-concrete bond strength using ANFIS-based fuzzy algorithm

A Kumar, HC Arora, K Kumar, H Garg - Expert Systems with Applications, 2023 - Elsevier
Nowadays, strengthening of reinforced concrete structures with a new class of sustainable
materials is the possible solution to retrofit the aged deteriorated structures. It is difficult to …

Big geospatial data or geospatial big data? a systematic narrative review on the use of spatial data infrastructures for big geospatial sensing data in public health

K Koh, A Hyder, Y Karale, MN Kamel Boulos - Remote Sensing, 2022 - mdpi.com
Background: Often combined with other traditional and non-traditional types of data,
geospatial sensing data have a crucial role in public health studies. We conducted a …

Multisource information fusion for real-time prediction and multiobjective optimization of large-diameter slurry shield attitude

X Wu, J Wang, Z Feng, H Chen, T Li, Y Liu - Reliability Engineering & …, 2024 - Elsevier
Abnormal large-diameter slurry shield attitudes (SA) lead to safety and quality problems in
shield construction. To achieve intelligent prediction and optimization of the large-diameter …

Long-term gridded land evapotranspiration reconstruction using Deep Forest with high generalizability

Q Feng, J Shen, F Yang, S Liang, J Liu, X Kuang… - Scientific Data, 2023 - nature.com
Previous datasets have limitations in generalizing evapotranspiration (ET) across various
land cover types due to the scarcity and spatial heterogeneity of observations, along with the …

Long-term effects of PM2. 5 components on hypertension: a national analysis in China

S Lv, Z Li, H Li, M Liu, Z Wu, S Yu, B Wu, B Gao… - Environmental …, 2023 - Elsevier
Background Evidence is less about the associations between fine particulate matter (PM
2.5) components and hypertension. We aimed to examine the long-term effects of PM 2.5 …

A machine learning and data analytics approach for predicting evacuation and identifying contributing factors during hazardous materials incidents on railways

H Ebrahimi, F Sattari, L Lefsrud, R Macciotta - Safety science, 2023 - Elsevier
An emergency evacuation order might be issued in response to a railway incident involving
hazardous materials (hazmat), such as the February 2023 derailment at Palestine, Ohio …

Implementation of deep neural networks and statistical methods to predict the resilient modulus of soils

R Polo-Mendoza, J Duque, D Mašín… - … Journal of Pavement …, 2023 - Taylor & Francis
ABSTRACT The Resilient Modulus (Mr) is perhaps the most relevant and widely used
parameter to characterise the soil behaviour under repetitive loading for pavement …

A European-scale analysis reveals the complex roles of anthropogenic and climatic factors in driving the initiation of large wildfires

C Ochoa, A Bar-Massada, E Chuvieco - Science of the total environment, 2024 - Elsevier
Analysing wildfire initiation patterns and identifying their primary drivers is essential for the
development of more efficient fire prevention strategies. However, such analyses have …