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Neurocomputing (Amsterdam), ISSN 0925-2312, 07/2016, Volume 197, pp. 53 - 68
In this paper, an efficient weighted Lagrangian ε-twin support vector regression with quadratic loss functions (WL-ε-TSVR) has been proposed. In our WL-ε... 
Regression | Weighted coefficient | ε-twin support vector machine | Quadratic cost function | Lagrangian functions | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Training | Support vector machines | Algorithms | Outliers (statistics) | Data sets | Weight reduction | Benchmarking | Optimization
Journal Article
Journal Article
PloS one, ISSN 1932-6203, 2019, Volume 14, Issue 9, pp. e0223223 - e0223223
... using a state-space model based support vector regression approach. PLoS ONE 14(4): e0214866. pmid:30951535... 
Education grants | Analysis | Models | Support vector machines | Regression models | Roads | State space models | Traffic accidents | Index Medicus
Journal Article
Neurocomputing (Amsterdam), ISSN 0925-2312, 10/2016, Volume 211, pp. 84 - 97
Journal Article
Neural networks, ISSN 0893-6080, 07/2015, Volume 67, pp. 140 - 150
The ν-Support Vector Regression (ν-SVR) is an effective regression learning algorithm, which has the advantage of using a parameter ν... 
Incremental learning | [formula omitted]-Support Vector Regression | Support vector machine | Online learning | ν-Support Vector Regression | Linear Models | Algorithms | Support Vector Machine | Machine Learning | Humans | Normal Distribution | Index Medicus
Journal Article
IEEE Sensors Journal, ISSN 1530-437X, 02/2015, Volume 15, Issue 2, pp. 850 - 854
Journal Article
Catena (Giessen), ISSN 0341-8162, 10/2015, Volume 133, pp. 266 - 281
.... The main aim of this study is to explore potential applications of two new models such as two-class Kernel Logistic Regression (KLR... 
Support vector machines | Two-class kernel logistic regression | Landslide | Alternative decision tree | China | Yihuang area | Landslides | Data mining | Analysis | Sediment transport | Decision-making | Construction | Regression | Mathematical models | Decision trees | Logistics
Journal Article
Applied energy, ISSN 0306-2619, 05/2019, Volume 242, pp. 403 - 414
.... Data-driven approaches, such as artificial neural networks, support vector regression, gradient boosting regression and extreme learning machine are the most advanced methods for building energy prediction... 
Support vector regression | Building energy consumption prediction | Data-driven | Vector field | Engineering | Engineering, Chemical | Technology | Energy & Fuels | Science & Technology
Journal Article
Reliability engineering & system safety, ISSN 0951-8320, 06/2016, Volume 150, pp. 210 - 221
Journal Article
Renewable energy, ISSN 0960-1481, 01/2016, Volume 85, pp. 790 - 809
In this paper, a hybrid methodology based on Support Vector Regression for wind speed forecasting is proposed... 
Support vector regression | Phase space reconstruction | Non-linear analysis | Wind speed forecasting | Genetic algorithms | Models | Algorithms | Wind power | Buildings and facilities | Analysis | Methods | Genetic vectors | Machine learning
Journal Article