Constructing observational learning agents using self-organizing maps
Sign Up to like & getrecommendations! Published in 2019 at "Artificial Life and Robotics"
DOI: 10.1007/s10015-019-00574-6
Abstract: Observational learning is a form of social learning whose theory proposes that new behaviors can be acquired through observing and imitating others. We employed Kohonen self-organizing maps to create observational learning agents to model the… read more here.
Keywords: learning; observational learning; organizing maps; self organizing ... See more keywords
Analysis of the uncharted, druglike property space by self-organizing maps.
Sign Up to like & getrecommendations! Published in 2021 at "Molecular diversity"
DOI: 10.1007/s11030-021-10343-y
Abstract: Physicochemical properties are fundamental to predict the pharmacokinetic and pharmacodynamic behavior of drug candidates. Easily calculated descriptors such as molecular weight and logP have been found to correlate with the success rate of clinical trials.… read more here.
Keywords: property space; space; chemical space; property ... See more keywords
Analysis of earthquake-induced groundwater level change using self-organizing maps
Sign Up to like & getrecommendations! Published in 2019 at "Environmental Earth Sciences"
DOI: 10.1007/s12665-019-8473-z
Abstract: For a better understanding of possible physical links between geophysical observables and earthquake characteristics, it is important to analyze statistical spatiotemporal patterns in nature related to such events. For this purpose, characteristic changes in groundwater… read more here.
Keywords: groundwater level; level; organizing maps; analysis earthquake ... See more keywords
Unraveling the occurrence of contaminants of emerging concern in groundwater from urban setting: A combined multidisciplinary approach and self-organizing maps.
Sign Up to like & getrecommendations! Published in 2022 at "Chemosphere"
DOI: 10.1016/j.chemosphere.2022.134395
Abstract: In recent decades, changes in human behavior and new technologies have introduced thousands of new compounds into the environment called "contaminants of emerging concern" (CEC). These compounds have been detected in different environmental compartments such… read more here.
Keywords: contaminants emerging; groundwater; emerging concern; organizing maps ... See more keywords
Revealing the relationships between the energy parameters of single-family buildings with the use of Self-Organizing Maps
Sign Up to like & getrecommendations! Published in 2018 at "Energy and Buildings"
DOI: 10.1016/j.enbuild.2018.08.028
Abstract: Abstract With a large number of factors affecting the energy efficiency of buildings, the importance of analyzing the growing amount of data becomes important. The aim of this research is to check whether the use… read more here.
Keywords: energy; use self; single family; organizing maps ... See more keywords
Using self-organizing maps in airborne geophysical data for mapping mafic dyke swarms in NE Brazil
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Applied Geophysics"
DOI: 10.1016/j.jappgeo.2021.104377
Abstract: Abstract Mapping widespread dyke swarms shed light on the tectonic processes that culminate in continental fragmentation, especially in the early phases of the crustal extension and magma emplacement . Airborne magnetic data are an effective… read more here.
Keywords: airborne geophysical; organizing maps; dyke swarms; self organizing ... See more keywords
Distinguishing Chemically Similar Polyamide Materials with ToF-SIMS Using Self-Organizing Maps and a Universal Data Matrix.
Sign Up to like & getrecommendations! Published in 2018 at "Analytical chemistry"
DOI: 10.1021/acs.analchem.8b01951
Abstract: Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is advancing rapidly, providing instruments with growing capabilities and resolution. The data sets generated by these instruments are likewise increasing dramatically in size and complexity. Paradoxically, methods for efficient… read more here.
Keywords: data sets; organizing maps; ion; tof sims ... See more keywords
Self-organizing maps of typhoon tracks allow for flood forecasts up to two days in advance
Sign Up to like & getrecommendations! Published in 2020 at "Nature Communications"
DOI: 10.1038/s41467-020-15734-7
Abstract: Typhoons are among the greatest natural hazards along East Asian coasts. Typhoon-related precipitation can produce flooding that is often only predictable a few hours in advance. Here, we present a machine-learning method comparing projected typhoon… read more here.
Keywords: two days; typhoon; days advance; typhoon tracks ... See more keywords
Survival Risk Prediction of Esophageal Cancer Based on Self-Organizing Maps Clustering and Support Vector Machine Ensembles
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3007785
Abstract: This article provides a method based on self-organizing maps (SOM) neural network clustering and support vector machine (SVM) ensembles to predict the survival risk levels of esophageal cancer. Nine blood indexes related to patient survival… read more here.
Keywords: organizing maps; risk; based self; prediction ... See more keywords
AW-SOM, an Algorithm for High-Speed Learning in Hardware Self-Organizing Maps
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2019.2909117
Abstract: Self-Organizing Maps (SOM) represent one of the most used clustering algorithms. A strong limitation in hardware SOM implementations is the decrease in processing speed when the number of neurons and features increase. For this reason,… read more here.
Keywords: speed; organizing maps; hardware; som algorithm ... See more keywords
Comparison of Classifier Architectures for Online Neural Spike Sorting
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2016.2641499
Abstract: High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission… read more here.
Keywords: classification; spike sorting; organizing maps; spike ... See more keywords