Discovering key factors and causalities impacting bridge pile resistance using Ensemble Bayesian networks: A bridge infrastructure asset management system
Bridges are one of the critical infrastructure systems and play a critical role in supporting the
economic development of nations. During the planning, design, and construction phases of …
economic development of nations. During the planning, design, and construction phases of …
Ann-based prediction of cone tip resistance with tabu-search optimization for geotechnical engineering applications
M Al Khazaleh, M Bisharah - Asian Journal of Civil Engineering, 2023 - Springer
The present research employed an authentic multivariate dataset of J-CLAY/5/124 Jiangsu
clays from China to construct an artificial neural network (ANN) model for the purpose of …
clays from China to construct an artificial neural network (ANN) model for the purpose of …
Bayesian-based approaches to exploring the long-term alteration in trace metals of surface water and its driving forces
Trace metal pollution poses a serious threat to the aquatic ecosystem. Therefore,
characterizing the long-term environmental behavior of trace metals and their driving forces …
characterizing the long-term environmental behavior of trace metals and their driving forces …
Convolutional neural network and support vector machine for prediction of damage intensity to multi-storey prefabricated RC buildings
A Jędrzejczyk, K Firek, J Rusek - Energies, 2022 - mdpi.com
This paper presents the results of a comparative analysis of Convolutional Neural Network
(CNN) and Support Vector Machine (SVM) models created for the prediction of the extent …
(CNN) and Support Vector Machine (SVM) models created for the prediction of the extent …
Governance and sustainability of distributed continuum systems: A big data approach
Distributed computing continuum systems (DCCS) make use of a vast number of computing
devices to process data generated by edge devices such as the Internet of Things and …
devices to process data generated by edge devices such as the Internet of Things and …
Impact of physicochemical and microbial drivers on the formation of disinfection by-products in drinking water distribution systems: A multivariate Bayesian network …
The formation of disinfection byproducts (DBPs) in drinking water distribution systems
(DWDS) is significantly affected by numerous factors, including physicochemical water …
(DWDS) is significantly affected by numerous factors, including physicochemical water …
BNSL GOBNILP algorithm in application to damage intensity prognostic system to RC multistorey residential buildings subjected to negative impacts of the industrial …
Paper presents a method of predicting the damage intensity of multifamily prefabricated RC
buildings located in the range of impacts of the industrial environment of mines. The …
buildings located in the range of impacts of the industrial environment of mines. The …
A prediction model for surface deformation caused by underground mining based on spatio-temporal associations
Accurate predictions of the surface deformation caused by underground mining are crucial
for the safe development of underground resources. Although surface deformation has been …
for the safe development of underground resources. Although surface deformation has been …
Selected artificial intelligence methods in the risk analysis of damage to masonry buildings subject to long-term underground mining exploitation
This paper presents an advanced computational approach to assess the risk of damage to
masonry buildings subjected to negative kinematic impacts of underground mining …
masonry buildings subjected to negative kinematic impacts of underground mining …
Applying Bayesian belief networks to assess alpine grassland degradation risks: a case study in northwest sichuan, China
S Zhou, L Peng - Frontiers in Plant Science, 2021 - frontiersin.org
Grasslands are crucial components of ecosystems. In recent years, owing to certain natural
and socio-economic factors, alpine grassland ecosystems have experienced significant …
and socio-economic factors, alpine grassland ecosystems have experienced significant …