Zobrazeno 1 - 10
of 947
pro vyhledávání: '"alternating decision tree"'
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 35, Iss 1, Pp 1-19 (2024)
Abstract Globally, but especially in the Chinese Loess Plateau, landslides are considered to be one of the most severe and significant geological hazards. The purpose of this study is to design two ensemble machine learning methods, which are denoted
Externí odkaz:
https://doaj.org/article/75f60930ee2f48d9a5186d41580f6b60
Akademický článek
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Autor:
Shimaa M. Abd-Elsalam, Mohamed M. Ezz, Shehab Gamalel-Din, Gamal Esmat, Ahmed Salama, Mahmoud ElHefnawi
Publikováno v:
Informatics in Medicine Unlocked, Vol 20, Iss , Pp 100421- (2020)
The standard method for diagnosing varices by upper endoscopy is invasive, costly, and has many drawbacks. To overcome these drawbacks, this study aims to build a predictive Esophageal Varices diagnosing model that uses a minimum number of the most s
Externí odkaz:
https://doaj.org/article/d97d9883c24b4f65ad54df80ae1aafb9
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 8, Iss 2, Pp 950-973 (2017)
The main purpose of this paper is to explore some potential applications of sophisticated machine learning techniques such as the kernel logistic regression, Naïve-Bayes tree and alternating decision tree models for landslide susceptibility analysis
Externí odkaz:
https://doaj.org/article/d6860dcae07b4576960a9fc107c696dc
Akademický článek
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Publikováno v:
Nuclear Engineering and Technology, Vol 53, Iss 12, Pp 4072-4079 (2021)
This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4774abff06aa47af78cc82be3341fb92
https://doi.org/10.1016/j.net.2021.06.020
https://doi.org/10.1016/j.net.2021.06.020
Autor:
Wei Chen, Yang Li, Paraskevas Tsangaratos, Himan Shahabi, Ioanna Ilia, Weifeng Xue, Huiyuan Bian
Publikováno v:
Applied Sciences, Vol 10, Iss 2, p 425 (2020)
This study presents a methodology for constructing groundwater spring potential maps by kernel logistic regression, (KLR), random forest (RF), and alternating decision tree (ADTree) models. The analysis was based on data concerning groundwater spring
Externí odkaz:
https://doaj.org/article/e629416f3fb0460bb6900d5e9dc632ec
Akademický článek
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Autor:
Thomas M. Peters, Kirsten Koehler, Christopher Zuidema, Konstantin Medvedovsky, Andrew N. Patton
Publikováno v:
Ann Work Expo Health
Occupational exposure assessments are dominated by small sample sizes and low spatial and temporal resolution with a focus on conducting Occupational Safety and Health Administration regulatory compliance sampling. However, this style of exposure ass
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ed41613238efbc1e440024c47f92693
https://doi.org/10.1093/annweh/wxab105
https://doi.org/10.1093/annweh/wxab105
Publikováno v:
Information Fusion. 75:186-196
Deep neural nets (DNNs) mostly tend to outperform other machine learning (ML) approaches when the training data is abundant, high-dimensional, sparse, or consisting of raw data (e.g., pixels). For datasets with other characteristics – for example,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d6351163088f8a0de1682e3780dd50b
https://doi.org/10.1016/j.inffus.2021.06.005
https://doi.org/10.1016/j.inffus.2021.06.005