Suchergebnisse - "Support Vector Regression algorithm"

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

Microseism Detection Method in Coal Mine Based on Spatiotemporal Characteristics and Support Vector Regression Algorithm

Autoren: Hong Gao Chaomin Mu Hui Sun

Quelle: Applied Sciences ; Volume 13 ; Issue 17 ; Pages: 9917

Schlagwörter: coal mine microseism, spatiotemporal characteristics, feature extraction, Markov chain, support vector regression algorithm, particle swarm optimization

Geographisches Schlagwort: agris

Dateibeschreibung: application/pdf

Relation: Earth Sciences; https://dx.doi.org/10.3390/app13179917

Verfügbarkeit: https://doi.org/10.3390/app13179917

A Novel Adaptive Weighted Least Square Support Vector Regression Algorithm-Based Identification of the Ship Dynamic Model

Autoren: Man Zhu Yuanqiao Wen Wuqiang Sun et al.

Quelle: IEEE Access, Vol 7, Pp 128910-128924 (2019)

Schlagwörter: Ship dynamics modeling, least square support vector regression algorithm, 0103 physical sciences, adaptive weight, artificial bee colony algorithm, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, outlier detection, robust 3σ principle, 01 natural sciences, TK1-9971, 0201 civil engineering

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08827492.pdf
https://doaj.org/article/be5422dac2f44c8897bb27222ef08d9c
https://ieeexplore.ieee.org/document/8827492
https://dblp.uni-trier.de/db/journals/access/access7.html#ZhuWSW19

Extended State Observer-Based Parameter Identification of Response Model for Autonomous Vessels

Autoren: Man Zhu Wuqiang Sun Yuanqiao Wen et al.

Quelle: Journal of Marine Science and Engineering, Vol 10, Iss 1291, p 1291 (2022)

Schlagwörter: autonomous vessels, linear response model, parameter identification, extended state observer (ESO), robust weighted least square support vector regression algorithm (RW-LSSVR), Naval architecture. Shipbuilding. Marine engineering, VM1-989, Oceanography, GC1-1581

Relation: https://www.mdpi.com/2077-1312/10/9/1291; https://doaj.org/toc/2077-1312; https://doaj.org/article/d145103abe2046859ed6596f1a75f22b

Verfügbarkeit: https://doi.org/10.3390/jmse10091291
https://doaj.org/article/d145103abe2046859ed6596f1a75f22b

Hybrids of Support Vector Regression with Grey Wolf Optimizer and Firefly Algorithm for Spatial Prediction of Landslide Susceptibility

Autoren: Ru Liu Jianbing Peng Yanqiu Leng et al.

Quelle: Remote Sensing, Vol 13, Iss 4966, p 4966 (2021)

Schlagwörter: landslide susceptibility, support vector regression algorithm, grey wolf optimizer algorithm, firefly algorithm, hybrid model, Science

Relation: https://www.mdpi.com/2072-4292/13/24/4966; https://doaj.org/toc/2072-4292; https://doaj.org/article/4aeb00b46d35405ea5b43fa73978d8b5

Verfügbarkeit: https://doi.org/10.3390/rs13244966
https://doaj.org/article/4aeb00b46d35405ea5b43fa73978d8b5

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

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

Quelle: RBRH, Volume: 30, Article number: e23, Published: 26 MAY 2025. May 2025

Schlagwörter: Artificial Intelligence techniques, Data-driven intelligent models, Fuzzy C-Means algorithm, Hydrological modeling, Support Vector Regression algorithm, Técnicas de Inteligência Artificial, Modelos inteligentes de análise de séries temporais. Algoritmo Fuzzy C-Means, Modelagem hidrológica, Algoritmo de Regressão por Vetores de Suporte

Dateibeschreibung: text/html

Zugangs-URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312025000100218&lng=en&tlng=en

Energy Assessment and Diagnosis of Variable Refrigerant Flow System Based on SVR-OCSVM Model

Autoren: Liu Jiahui Liu Jiangyan Chen Huanxin et al.

Quelle: Zhileng xuebao, Vol 41 (2020)

Schlagwörter: variable refrigerant flow system, energy assessment and diagnosis, support vector regression algorithm, one-class support vector machine, Heating and ventilation. Air conditioning, TH7005-7699, Low temperature engineering. Cryogenic engineering. Refrigeration, TP480-498, Technology

Dateibeschreibung: electronic resource

Relation: http://www.zhilengxuebao.com/thesisDetails#10.3969/j.issn.0253-4339.2020.04.075; https://doaj.org/toc/0253-4339

Zugangs-URL: https://doaj.org/article/2417506a55ab42ee8fb7578420164677

Optimized Support Vector Regression Model Based on Particle Swarm Optimization for Energy Consumption Prediction of a Variable Refrigerant Flow System

Autoren: Li Yujin Chen Huanxin Liu Jiangyan

Quelle: Zhileng xuebao, Vol 40 (2019)

Schlagwörter: variable refrigerant flow rate system, prediction model, operating power, particle swarm optimization, support vector regression algorithm, Heating and ventilation. Air conditioning, TH7005-7699, Low temperature engineering. Cryogenic engineering. Refrigeration, TP480-498, Technology

Dateibeschreibung: electronic resource

Relation: http://www.zhilengxuebao.com/thesisDetails#10.3969/j.issn.0253-4339.2019.06.053; https://doaj.org/toc/0253-4339

Zugangs-URL: https://doaj.org/article/e942a2f2ba7443a58a78c95f1b46944f

Crack detection in a pipe by adaptive subspace iteration algorithm and least square support vector regression

Autoren: Wang, Youming Wu, Qing

Quelle: Journal of Vibroengineering, Vol. 16, Issue 6, 2014, p. 2800-2812.; 1392-8716; 2538-8460

Index Begriffe: pipe crack, multiwavelet, adaptive subspace iteration algorithm, least square support vector regression algorithm, Research article

URL: https://www.extrica.com/article/15057