Architectural spatial layout planning using artificial intelligence
Spatial layout planning in architecture requires a deep understanding of topological spatial
relationships, yet the process remains repetitive and laborious for designers. However …
relationships, yet the process remains repetitive and laborious for designers. However …
SSI-LSTM network for adaptive operational modal analysis of building structures
HB Shim, HS Park - Mechanical Systems and Signal Processing, 2023 - Elsevier
Various operational modal analysis (OMA) methods have been developed to identify the
modal parameters of buildings in use. Recently, efforts have been expended to solve the …
modal parameters of buildings in use. Recently, efforts have been expended to solve the …
[HTML][HTML] MetaRF: attention-based random forest for reaction yield prediction with a few trails
Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many
impressive applications, but the success of these applications requires a massive amount of …
impressive applications, but the success of these applications requires a massive amount of …
[图书][B] Projection-based clustering through self-organization and swarm intelligence: combining cluster analysis with the visualization of high-dimensional data
MC Thrun - 2018 - books.google.com
This open access book covers aspects of unsupervised machine learning used for
knowledge discovery in data science and introduces a data-driven approach to cluster …
knowledge discovery in data science and introduces a data-driven approach to cluster …
[HTML][HTML] An experimental research on the use of recurrent neural networks in landslide susceptibility mapping
Natural hazards have a great number of influencing factors. Machine-learning approaches
have been employed to understand the individual and joint relations of these factors …
have been employed to understand the individual and joint relations of these factors …
[HTML][HTML] Outlier analysis for accelerating clinical discovery: An augmented intelligence framework and a systematic review
Clinical discoveries largely depend on dedicated clinicians and scientists to identify and
pursue unique and unusual clinical encounters with patients and communicate these …
pursue unique and unusual clinical encounters with patients and communicate these …
Modeling biohydrogen production using different data driven approaches
Three modeling techniques namely multilayer perceptron artificial neural network
(MLPANN), microbial kinetic with Levenberg-Marquardt algorithm (MKLMA) developed from …
(MLPANN), microbial kinetic with Levenberg-Marquardt algorithm (MKLMA) developed from …
On the Use of t‐Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson's Disease
FHM Oliveira, ARP Machado… - … methods in medicine, 2018 - Wiley Online Library
Parkinson's disease (PD) is a neurodegenerative disorder that remains incurable. The
available treatments for the disorder include pharmacologic therapies and deep brain …
available treatments for the disorder include pharmacologic therapies and deep brain …
Evolutionary generalized radial basis function neural networks for improving prediction accuracy in gene classification using feature selection
F Fernández-Navarro, C Hervás-Martínez, R Ruiz… - Applied Soft …, 2012 - Elsevier
Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in
several function approximation and pattern recognition problems. The use of different RBFs …
several function approximation and pattern recognition problems. The use of different RBFs …
[PDF][PDF] Effect of non-linear deep architecture in sequence labeling
M Wang, CD Manning - … of the Sixth International Joint Conference …, 2013 - aclanthology.org
If we compare the widely used Conditional Random Fields (CRF) with newly proposed
“deep architecture” sequence models (Collobert et al., 2011), there are two things changing …
“deep architecture” sequence models (Collobert et al., 2011), there are two things changing …