Zobrazeno 1 - 10
of 133
pro vyhledávání: '"SHapley additive explanation (SHAP)"'
Autor:
Fei Wang, Yuanxin Lin, Lian Qin, Xiangtai Zeng, Hancheng Jiang, Yanlan Liang, Shifeng Wen, Xiangzhi Li, Shiping Huang, Chunxiang Li, Xiaoyu Luo, Xiaobo Yang
Publikováno v:
Environment International, Vol 195, Iss , Pp 109203- (2025)
Background: Exposure to per- and polyfluoroalkyl substances (PFAS) may linked to thyroid cancer (TC) risk, but inconsistent findings and a lack of studies on mixed exposures exist, especially regarding novel PFAS compounds. Additionally, little is kn
Externí odkaz:
https://doaj.org/article/d9bbfd7fa75f464c92198d02e970fc13
Publikováno v:
Ecological Indicators, Vol 166, Iss , Pp 112551- (2024)
Investigating the nonlinear impacts of urban landscape and climatic parameters on urban temperatures, a critical issue within urban climatology. Chengdu, characterized by its hot, rainy summers and rapid urban development, serves as an ideal model to
Externí odkaz:
https://doaj.org/article/0c6785a546054161aad8e9080366b982
Autor:
Mohammed, Safwan a, b, ⁎, Arshad, Sana c, Bashir, Bashar d, Ata, Behnam e, Al-Dalahmeh, Main f, Alsalman, Abdullah d, Ali, Haidar g, Alhennawi, Sami g, Kiwan, Samer g, Harsanyi, Endre a, b
Publikováno v:
In Journal of Environmental Management November 2024 370
Autor:
Ghose, Partho d, Oliullah, Khondokar a, Mahbub, Md Kawsher b, ⁎, Biswas, Milon c, Uddin, Kazi Nur b, Jamil, Hasan M. d
Publikováno v:
In Expert Systems With Applications 15 March 2025 265
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 11115 (2024)
This study aims to identify the factors that influence the occurrence of traffic accidents to improve motorway traffic safety. Various data, including the frequency of traffic accidents, traffic volume, geometric structure, and congestion level, were
Externí odkaz:
https://doaj.org/article/c8f792a660ac4dcca2f0dc1650e9065d
Publikováno v:
Case Studies in Construction Materials, Vol 20, Iss , Pp e03325- (2024)
In this study, the properties of controlled low strength material (CLSM) made from waste soil were examined, utilizing 53 different mix proportions, and a dataset was subsequently constructed. Models, such as particle swarm optimization (PSO)-support
Externí odkaz:
https://doaj.org/article/baf50a54ab9c40b4a52c7b171d0e01c1
A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 14, Iss 1 (2023)
AbstractThe quality of samples is crucial in constructing a data-driven landslide susceptibility model. This article aims to construct a data-driven landslide susceptibility model that takes into account the selection of non-landslide samples. First,
Externí odkaz:
https://doaj.org/article/bb016fa7dd7a4069a7721e0d6e5572d4
Publikováno v:
Frontiers in Endocrinology, Vol 14 (2023)
ObjectiveTo screen for predictive obesity factors in overweight populations using an optimal and interpretable machine learning algorithm.MethodsThis cross-sectional study was conducted between June 2011 and January 2012. The participants were random
Externí odkaz:
https://doaj.org/article/c307e3cc6eb743e1b0510992dde6fdba
Autor:
Seongmun Sim, Jungho Im
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 7819-7837 (2023)
Ocean–fog is a type of fog that forms over the ocean and has a visibility of less than 1 km. Ocean–fog frequently causes incidents over oceanic and coastal regions; ocean–fog detection is required regardless of the time of day. Ocean–fog has
Externí odkaz:
https://doaj.org/article/af966642bb9a4fb3a3f15fd077f78ad4
Autor:
Nikos Kostopoulos, Dimitris Kalogeras, Dimitris Pantazatos, Maria Grammatikou, Vasilis Maglaris
Publikováno v:
IEEE Access, Vol 11, Pp 61144-61160 (2023)
Domain Generation Algorithms (DGA’s) have been employed by botnet orchestrators for controlling infected hosts (bots), while evading detection by performing multiple DNS requests, mostly for non-existing domain names. With blacklists ineffective, m
Externí odkaz:
https://doaj.org/article/f0b8e316cc3c4ae8807983cada45fb47