Suchergebnisse - "regression algorithm"

Machine learning-optimized compact dual-band medical syringe-inspired wearable antenna for efficient WBAN applications

Autoren: Muhammad S. Yahya Umar Musa Mohammad S. Zidan et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-24 (2025)

Schlagwörter: Machine learning, Wearable antenna, Wireless body area network (WBAN), Dual-band, Regression algorithm, Specific absorption rate (SAR), Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/e55cba2349c34ff393c0af0bf0b1738f

Recovering 3D Basin Basement Relief Using High-Precision Magnetic Data Through Particle Swarm Optimization and Back Propagation Algorithm

Autoren: Shen Yan Xinjun Zhang Zhongda Shang et al.

Quelle: IEEE Access, Vol 13, Pp 44343-44353 (2025)

Schlagwörter: numerical simulation, PSO-BP neural network regression algorithm, Magnetic substrate interface, Electrical engineering. Electronics. Nuclear engineering, potential field processing conversion, TK1-9971

Zugangs-URL: https://doaj.org/article/eab99bb36b3c4fc2a3033e54a71020b8

Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study

Autoren: Ziwei Yang Xiao Liang Yuqi Ji et al.

Quelle: J Pain Res
Journal of Pain Research, Vol Volume 18, Pp 271-282 (2025)

Schlagwörter: resting-state functional mri, Medicine (General), R5-920, radiomic, low-back-related leg pain, cognitive impairment, logistic regression algorithm, Original Research

Zugangs-URL: https://doaj.org/article/a09db0d17ecf4274a78978a1160c0b1f

Predicting specific wear rate of laser powder bed fusion AlSi10Mg parts at elevated temperatures using machine learning regression algorithm: Unveiling of microstructural morphology analysis

Autoren: Vijaykumar S. Jatti R. Murali Krishnan A. Saiyathibrahim et al.

Quelle: Journal of Materials Research and Technology, Vol 33, Iss, Pp 3684-3695 (2024)

Schlagwörter: Gaussian Process Regression algorithm, Specific Wear Rate, Mining engineering. Metallurgy, Machine Learning Regression Algorithm, Laser powder bed fusion, Specific wear rate, TN1-997, Laser Powder Bed Fusion, Machine learning regression algorithm, Prediction, MAE, RMSE

Zugangs-URL: https://doaj.org/article/3a2c2dfb50b6409594a00b9327819c0b

Hyperspectral imaging technology for determining soluble solids content in Dangshansuli pears with CPO-PLSR modeling optimization

Autoren: CHU Jiahui MENG Qinghua WU Zhefeng et al.

Quelle: Guoshu xuebao, Vol 42, Iss 9, Pp 2179-2191 (2025)

Schlagwörter: dangshansuli pear, hyperspectral imaging, soluble solids content, crowned hares optimization algorithm, partial least squares regression algorithm, Botany, QK1-989, Agriculture

Dateibeschreibung: electronic resource

Relation: http://fruitsci.zzgss.cn/english/upload/down/month_2509/250920250918.pdf; https://doaj.org/toc/1009-9980

Zugangs-URL: https://doaj.org/article/b012b800c5164fb5adda64841a54befa

Efficacy of machine learning algorithm in estimating oxyhydrogen gas generation system: Electrolyte concentration and current influence on sustainable energy production

Autoren: Subramanian, Balaji Sridharan, Naveen Venkatesh Vaithiyanathan, Sugumaran et al.

Quelle: Process Safety and Environmental Protection. 191:2292-2302

Schlagwörter: Machine Learning, Regression Algorithm, Hydrogen Production, Alternating Model Tree

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/20.500.12713/7394

Proposing a framework for body mass prediction with point clouds: A study applied in typical swine pen environments

Autoren: Gabriel Pagin Luciane Silva Martello Rubens André Tabile et al.

Quelle: Smart Agricultural Technology, Vol 12, Iss , Pp 101200- (2025)

Schlagwörter: 3D imaging, Animal performance, Attribute selection, Feature extraction, Regression algorithm, Agriculture (General), S1-972, Agricultural industries, HD9000-9495

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2772375525004319; https://doaj.org/toc/2772-3755

Zugangs-URL: https://doaj.org/article/759dc2ac22f44213a83449e76dc1507c

Comparative analysis of optimized logistic regression with state-of-the-art models for complex gastroenterological image analysis

Autoren: Daniela-Maria Cristea Ioan Sima Laszlo Barna Iantovics

Quelle: Frontiers in Medicine, Vol 12 (2025)

Schlagwörter: gastrointestinal polyps, colorectal disease, machine learning, logistic regression algorithm, multinomial classifier, random forest, Medicine (General), R5-920

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fmed.2025.1655612/full; https://doaj.org/toc/2296-858X

Zugangs-URL: https://doaj.org/article/cccca274426343c4a1c825dacfddca00

TabNet-driven interpretable prediction of multi-oxide composition in cement using NIR spectroscopy

Autoren: GeZhiChen Li

Quelle: Frontiers in Chemistry, Vol 13 (2025)

Schlagwörter: cement raw meal, near-infrared (NIR) spectroscopy, deep learning, oxides prediction, regression algorithm, Chemistry, QD1-999

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fchem.2025.1691413/full; https://doaj.org/toc/2296-2646

Zugangs-URL: https://doaj.org/article/dc2b9f7c16894b31970e3da10a30c5f7

Nomogram for predicting the severity of high-risk plaques in acute coronary syndrome

Autoren: Miao-Na Bai Ji-Xiang Wang Xiao-Wei Li et al.

Quelle: Front Cardiovasc Med
Frontiers in Cardiovascular Medicine, Vol 12 (2025)

Schlagwörter: nomogram, optical coherence tomography, LASSO regression algorithm, RC666-701, Diseases of the circulatory (Cardiovascular) system, high-risk plaque, Cardiovascular Medicine, acute coronary syndrome

Zugangs-URL: https://doaj.org/article/3c293b39c8c840d4baf1d87ace3679a5

Comparison of Machine Learning Algorithms for Predicting Stunting Prevalence in Indonesia

Autoren: Moh. Asry Eka Pratama Syaiful Hendra Hajra Rasmita Ngemba et al.

Quelle: Jurnal Sisfokom, Vol 13, Iss 2, Pp 200-209 (2024)

Schlagwörter: machine learning, stunting prevalence, stunting, regression algorithm, Information technology, tableau, T58.5-58.64, 3. Good health

Zugangs-URL: https://doaj.org/article/e7275c8639af4f9499a93c9b9514e82e

Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study

Autoren: Yang Z Liang X Ji Y et al.

Quelle: Journal of Pain Research, Vol 18, Pp 271-282 (2025)

Schlagwörter: cognitive impairment, resting-state functional mri, low-back-related leg pain, radiomic, logistic regression algorithm, Medicine (General), R5-920

Dateibeschreibung: electronic resource

Relation: https://www.dovepress.com/hippocampal-functional-radiomic-features-for-identification-of-the-cog-peer-reviewed-fulltext-article-JPR; https://doaj.org/toc/1178-7090

Zugangs-URL: https://doaj.org/article/a09db0d17ecf4274a78978a1160c0b1f

Smart Delivery Assignment through Machine Learning and the Hungarian Algorithm

Autoren: Juan Pablo Vásconez Elias Schotborgh Ingrid Nicole Vásconez et al.

Quelle: Smart Cities, Vol 7, Iss 3, Pp 1109-1125 (2024)

Schlagwörter: I460 - Machine learning, regression model, 0211 other engineering and technologies, 02 engineering and technology, Engineering (General). Civil engineering (General), machine learning, H671 - Robotics, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, machine learning-based, regression algorithm, smart delivery, TA1-2040, Hungarian optimization algorithm

Zugangs-URL: https://doaj.org/article/e26babdc30b74736b18d30586daa7803

Development and validation of a nomogram for predicting lung cancer based on acoustic–clinical features

Autoren: Zhou Lu Jiaojiao Sha Xunxia Zhu et al.

Quelle: Front Med (Lausanne)
Frontiers in Medicine, Vol 12 (2025)

Schlagwörter: nomogram, lung cancer, Medicine (General), machine learning, R5-920, acoustic diagnosis, lasso regression algorithm, Medicine

Zugangs-URL: https://doaj.org/article/b950b3b6d1334b3a8fcb091f010fafa2

Predicting Ethiopian gross domestic product using machine learning model

Autoren: Elisaye Bekele Temesgen Zekarias

Quelle: Journal of Science and Inclusive Development; Vol.6 No.2 Dec 2024; 17-42

Schlagwörter: Gross Domestic Product, Ethiopia Economy, Machine Learning, Predictive model evaluation, Regression algorithm, Macroeconomic indicators

Zugangs-URL: https://www.ajol.info/index.php/jsid/article/view/278443

Evaluating different strategies for machine learning training applied to flow forecasting based on clustering of flood events

Autoren: Patrícia Cristina Steffen Júlio Gomes Eloy Kaviski et al.

Quelle: Revista Brasileira de Recursos Hídricos, Vol 30 (2025)

Schlagwörter: TC401-506, Data-driven intelligent models, Technology, Hydraulic engineering, Hydrological modeling, Support Vector Regression algorithm, Artificial Intelligence techniques, River, lake, and water-supply engineering (General), Environmental sciences, Geography. Anthropology. Recreation, GE1-350, TC1-978, Fuzzy C-Means algorithm

Zugangs-URL: https://doaj.org/article/9e5024b51cff4a8a85095a4af0debb97

First Reported QSAR Models Of Dual HDAC6 And ROCK2 Inhibitors Employing Random Forest Regression Algorithm

Autoren: Zukić, Selma Beljkaš, Milan Maran, Uko et al.

Quelle: 21st International Conference on QSAR in Environmental and Health Sciences, June 6-9, 2025 | Milan, Italy, Book of Abstracts

Schlagwörter: multitarget-directed ligands, Histone deacetylases, Rho- associated protein kinases, Random Forest Regression Algorithm

Relation: info:eu-repo/grantAgreement/MESTD/inst-2020/200161/RS//; Cost Action, CA22125; Ministry of Education and Research, Republic of Estonia, through Estonian Research Council (grant number PRG1509); https://farfar.pharmacy.bg.ac.rs/handle/123456789/6349; http://farfar.pharmacy.bg.ac.rs/bitstream/id/18552/First_Reported_QSAR_pub_2025.pdf; https://hdl.handle.net/21.15107/rcub_farfar_6349

Verfügbarkeit: https://farfar.pharmacy.bg.ac.rs/handle/123456789/6349
http://farfar.pharmacy.bg.ac.rs/bitstream/id/18552/First_Reported_QSAR_pub_2025.pdf
https://hdl.handle.net/21.15107/rcub_farfar_6349

Estimating leaf and canopy nitrogen contents in major field crops across the growing season from hyperspectral images using nonparametric regression

Autoren: Wang, Dong Struik, Paul C. Liang, Lei et al.

Quelle: Computers and Electronics in Agriculture 233 (2025) ; ISSN: 0168-1699

Schlagwörter: Crop nitrogen management, Hyperspectral image, Leaf nitrogen trait, Major crop, Nonparametric regression algorithm

Dateibeschreibung: application/pdf

Relation: https://edepot.wur.nl/688677

Verfügbarkeit: https://research.wur.nl/en/publications/estimating-leaf-and-canopy-nitrogen-contents-in-major-field-crops
https://doi.org/10.1016/j.compag.2025.110147
https://edepot.wur.nl/688677

IoT-Integrated Machine Learning for Precision Watering in Bamboo Mushroom Farming

Autoren: Pinit Nuangpirom Siwasit Pitjamit Parida Jewpanya et al.

Quelle: International Journal of Integrated Engineering; Vol. 17 No. 1 (2025); 31-45 ; 2600-7916 ; 2229-838X

Schlagwörter: Bamboo mushroom, machine learning, regression algorithm, Internet of Thing

Dateibeschreibung: application/pdf

Relation: http://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/18207/7209; http://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/18207

Verfügbarkeit: http://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/18207

Insight into the Relationships Between Chemical, Protein and Functional Variables in the PBP/GOBP Family in Moths Based on Machine Learning

Autoren: Xaviera A. López-Cortés Gabriel Lara Nicolás Fernández et al.

Quelle: International Journal of Molecular Sciences ; Volume 26 ; Issue 5 ; Pages: 2302

Schlagwörter: chemical ecology, lepidoptera, odorant-binding proteins, artificial intelligence, ligand binding, regression algorithm

Geographisches Schlagwort: agris

Dateibeschreibung: application/pdf

Relation: Biochemistry; https://dx.doi.org/10.3390/ijms26052302

Verfügbarkeit: https://doi.org/10.3390/ijms26052302