Search Results - "support vector regression"

Enhanced quality prediction in laser powder bed fusion through data fusion-enabled regression analysis of spatter-related defects

Authors: Zhirnov, Ivan Krakhmalev, Pavel, Professor

Source: Journal of Manufacturing Processes. 152:293-307

Subject Terms: Data fusion, Defects, Density of gases, Forecasting, Gases, Process control, Shielding, Support vector regression, Surface roughness, Fusion defects, Gas velocity, Integrating information, Laser powder bed fusion, Laser powders, Powder bed, Quality prediction, Shielding gas, Spattering, Top surface, Quality assurance, Materialteknik, Materials Engineering, Maskinteknik, Mechanical Engineering

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-106651
https://doi.org/10.1016/j.jmapro.2025.08.013

Beyond boundaries: AI-optimized global landslide susceptibility mapping

Authors: Panahi, Mahdi Rezaie, Fatemeh Khosravi, Khabat et al.

Source: Geomatics, Natural Hazards and Risk. 16(1)

Subject Terms: bat algorithm, global scale, grey wolf optimizer, Landslide susceptibility map, support vector regression

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-363401
https://doi.org/10.1080/19475705.2025.2493222

Enhancing the accuracy of wind power projections under climate change using geospatial machine learning models

Authors: Moradian, S. Gharbia, S. Majidi Nezhad, Meysam et al.

Source: Energy Reports. 12:3353-3363

Subject Terms: Artificial intelligence, Climate change, Machine learning, Wind energy, Wind power, Adversarial machine learning, Wind forecasting, Energy, Geo-spatial, Machine learning models, Machine-learning, Neural-networks, Power, Power projection, Projection maps, Support vector regression models, Wind speed, Windmill

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-68528
https://doi.org/10.1016/j.egyr.2024.09.007

Estimation of Potato Water Footprint Using Machine Learning Algorithm Models in Arid Regions

Authors: Abdel-Hameed, Amal Mohamed Abuarab, Mohamed Al-Ansari, Nadhir et al.

Source: Potato Research. 67(4):1755-1774

Subject Terms: Artifcial neural network, Blue water footprint, Random forest, Support vector regression, Water management, Soil Mechanics, Geoteknik

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-104949
https://doi.org/10.1007/s11540-024-09716-1

Predicting design suitability of box-shaped sustainable timber structural members using machine learning and hyperparameter optimization

Authors: Muhammed Cosut Gebrail Bekdas Sinan Melih Nigdeli et al.

Contributors: Muhammed Cosut Gebrail Bekdas Sinan Melih Nigdeli et al.

Source: Neural Computing and Applications. 37:24123-24148

Subject Terms: Hyperparameter Optimization, Box-shaped Member, Support Vector Regression, Timber, Performance Metrices, Learning Systems, Structural Analysis, Machine Learning, Naive Bayes, Timber Structures, Energy Dissipation, Learning Algorithms, Structural Members, Logistic Regression, Machine-learning, Hyper-parameter Optimizations, Model Performance Metric, Decision Trees, Timber Structure, Logistics Regressions, Discriminant Analysis, Modeling Performance, Classification, Structural Optimization, Gaussians, Nearest Neighbor Search, Model Performance Metrics, Forecasting

Financial Inputs Prediction with Machine Learning and Covariance Matrix Applications

Authors: Harun Benli Peri Gunes Mert Ulkgun et al.

Source: 2025 IEEE 5th International Conference on Software Engineering and Artificial Intelligence (SEAI). :7-10

Subject Terms: Random Forests, Machine-Learning, Support Vector Regression, Sample Covariances, Risk Assessment, Electronic Trading, Insurance, Markowitz Modern Portfolio Theory, Budget Control, Portfolio Optimization, Markowitz, Investments, Financial Markets, Covariance Matrices, Based Covariance Estimation, Risk Management, Decision Trees, Statistics, Commerce, Modern Portfolio Theories, Forestry, Robo-Advisory Applications, Costs, Benchmarking, Robo-Advisory Application, Risk Perception, Covariance Matrix, Covariance Estimation, Forecasting

Influence of Input Features and EMG Type on Ankle Joint Torque Prediction With Support Vector Regression

Authors: Kizyte, Asta Lei, Yuchen Wang, Ruoli

Source: IEEE transactions on neural systems and rehabilitation engineering. 31:4286-4294

Subject Terms: Dynamic contraction, electromyography, joint torque, machine learning, support vector regression

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-340658
https://doi.org/10.1109/TNSRE.2023.3323364

Vahşi doğada para takibi: Türkiye av turizmi gelir tahmini için destek vektör regresyonundaki çekirdek fonksiyonlarının etkinliği

Authors: Deniz Kaya Nurbanu Bursa

Source: Volume: 12, Issue: 147-58
Turkish Journal of Forestry Research
Ormancılık Araştırma Dergisi

Subject Terms: Ormancılık Politikası, Ekonomisi ve Hukuku, Avcılık, av turizmi, çekirdek fonksiyonu, destek vektör regresyonu, turizm, Forestry Sciences (Other), Hunting, hunting tourism, kernel function, support vector regression, tourism, Forestry Politics, Economics and Law, Ormancılık (Diğer)

File Description: application/pdf

Access URL: https://dergipark.org.tr/tr/pub/ogmoad/issue/88542/1531543

Fast estimation of patient‐specific organ doses from abdomen and head CT examinations without segmenting internal organs using machine learning models

Authors: Wencheng Shao Liangyong Qu Xin Lin et al.

Source: Precision Radiation Oncology, Vol 9, Iss 2, Pp 77-86 (2025)

Subject Terms: Medical physics. Medical radiology. Nuclear medicine, segmentation‐free, R895-920, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, computed tomography, support vector regression, organ dose, radiomics features, RC254-282

Access URL: https://doaj.org/article/74753c2951ea4b8caca2a6a619f5a71f

Predicting Financial Market Volatility with Modern Model and Traditional Model

Authors: R. G. Aldeki

Source: Финансы: теория и практика, Vol 29, Iss 2, Pp 154-165 (2025)

Subject Terms: arch, garch-svr, garch, volatility forecasting, HG1-9999, classical volatility models, hybrid model, machine learning models, support vector regression, Finance

Access URL: https://doaj.org/article/44b1f653ebd345abb08e103c58213788

Harnessing Machine Learning for QSPR Modeling of Corrosion Inhibitors in HCl for Mild Steel Protection

Authors: Mohammed Bouziani Idrissi Idriss Moumen Sara Taghzouti et al.

Source: Current Analytical Chemistry. 21:356-373

Subject Terms: multilayer perceptron regression, machine learning, corrosion inhibitors, QSPR, random forest regression, support vector regression, mild steel, XGBoost

Access URL: https://hdl.handle.net/20.500.12418/29003

Impact-induced energy release of typical HCP metal/PTFE/W reactive materials: Experimental study and predictive modeling via machine learning

Authors: Zhenwei Zhang Weixi Tian Tianyi Wang et al.

Source: Defence Technology, Vol 47, Iss, Pp 124-138 (2025)

Subject Terms: Support vector regression, Military Science, HCP metal/PTFE/W, Reactive materials, Energy release efficiency, Impact-induced energy release

Access URL: https://doaj.org/article/2638cc03a65d43c4a06f41231a377458

Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models

Authors: Micheal Ayodeji Ogundero Taiwo Adelakin Kehinde Orolu et al.

Source: ABUAD Journal of Engineering Research and Development, Vol 8, Iss 1 (2025)

Subject Terms: Reservoir Flow Capacity, Machine Learning, Artificial Neural Network, Random Forest, Support Vector Regression, TA1-2040, Engineering (General). Civil engineering (General), Sand Production

Access URL: https://doaj.org/article/dd4285bc26da4ec2b6184b15eee01d39

Applications of deep learning techniques for predicting dynamic service location enhanced scheduling algorithm in foggy computing environment

Authors: Mengmeng Wang

Source: Alexandria Engineering Journal, Vol 117, Iss, Pp 183-192 (2025)

Subject Terms: Fog–edge computing, Support vector regression, Recurrent neural networks, Artificial neural networks, Convolutional neural networks, TA1-2040, Prediction, Engineering (General). Civil engineering (General)

Access URL: https://doaj.org/article/cfcd334a23e0499bab6ecdf7fe17993c

Data-driven models for building energy efficiency monitoring

Authors: Massana i Raurich, Joaquim

Contributors: University/Department: Universitat de Girona. Departament d'Enginyeria Elèctrica, Electrònica i Automàtica

Thesis Advisors: Pous i Sabadí, Carles

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Energia electrica, Electricity, Predicció del consum elèctric, Load prediction, Predicción del consumo eléctrico, Prediccions horàries de consum, Hourly consumption predictions, Predicciones horarias de consumo, Energy Management Systems (EMS), Smart Grids (SG), Support Vector Regression (SVR), Multiple Linear Regression (MLR), Artificial Neural Network (ANN)

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/482148

Predictive modelling on the compressive strength and fresh properties of self-compacting recycled aggregate concrete using machine learning approaches

Authors: Singh, T. Kapoor, K. Singh, S.P.

Source: Materiales de Construcción; Vol. 75 No. 358 (2025): Online first; e375
Materiales de Construcción; Vol. 75 Núm. 358 (2025): Número en curso; e375

Subject Terms: Perceptrón multicapa, K nearest neighbours regression, Regresión de vectores de soporte, Extreme gradient boost regression, Hormigón autocompactante con áridos reciclados, Regresión por gradiente ascendente extremo, Self compacting recycled aggregate concrete, Regresión por gradiente ascendente, Regresión por ensacado, K fold cross validation, Support vector regression, Gradient boost regression, Optimización multiobjetivo de Pareto, Multi objective pareto optimisation, Regresión por los K vecinos más cercanos, Validación cruzada K-fold, Multi layer perceptron, Bagging regression

File Description: application/pdf

Access URL: https://materconstrucc.revistas.csic.es/index.php/materconstrucc/article/view/3826

Proof-of-concept ensemble machine-learning forecasting of tensile properties in hybrid polypropylene composites reinforced with flax, basalt, and rice husk powder

Authors: Thanh Mai Nguyen Tran Duy Tran Quang Prabhakar M.N. et al.

Source: Discover Materials, Vol 5, Iss 1, Pp 1-23 (2025)

Subject Terms: Stacking, Support vector regression, XGBoost, Polypropylene hybrid composites, Rice husk powder, Materials of engineering and construction. Mechanics of materials, TA401-492

File Description: electronic resource

Relation: https://doaj.org/toc/2730-7727

Access URL: https://doaj.org/article/f40de76b939f4cd89a39ac0ad6417692

A study on parametric design of ceramic liquor bottles by combining grey relational analysis and particle swarm optimization support vector regression

Authors: Wei Guo Xing Lu Zhenwei Zhang

Source: Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Subject Terms: Traditional cultural product, Kansei engineering, Grey relational analysis, Particle swarm optimization-support vector regression, Ceramic liquor bottle, Medicine, Science

File Description: electronic resource

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

Access URL: https://doaj.org/article/d42837363326455ca67e2cfb6e2af46b

On data-driven optimization design of protective structures for vehicles against explosion

Authors: Shanyu XIAO Xiaowang SUN Weiwei QIN et al.

Source: Baozha yu Chongji, Vol 45, Iss 11, Pp 1-17 (2025)

Subject Terms: explosive protection structures, adversarial generating network, semi-supervised support vector regression, multi-objective optimization, Explosives and pyrotechnics, TP267.5-301

File Description: electronic resource

Relation: https://doaj.org/toc/1001-1455

Access URL: https://doaj.org/article/ab028ef97c814fb1956dc6bf1388d61f

Comparison of Support Vector Regression and Extreme Learning Machine Methods for Predicting Bitcoin Prices

Authors: Felix Ferdinand Ryan Anthony Tanjaya Jason Winata et al.

Source: Journal of Applied Informatics and Computing, Vol 9, Iss 5, Pp 2121-2130 (2025)

Subject Terms: bitcoin, support vector regression (svr), extreme learning machine (elm), predictio, comparison, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/10983; https://doaj.org/toc/2548-6861

Access URL: https://doaj.org/article/a1e329c202ec479296ca810fc07b30f8