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Copper Price Prediction Using Support Vector Regression Technique
Applied Sciences, 2020 Predicting copper price is essential for making decisions that can affect companies and governments dependent on the copper mining industry. Copper prices follow a time series that is nonlinear and non-stationary, and that has periods that change as a ...
Gabriel Astudillo +3 more
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Incremental Reduced Least Squares Twin Support Vector Regression
Jisuanji kexue yu tansuo, 2021 In the incremental least squares twin support vector regression, to solve the problem that the constituted kernel matrix cannot approximate the original kernel matrix well, this paper proposes an incremental reduced least squares twin support vector ...
CAO Jie, GU Binjie, XIONG Weili, PAN Feng
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On implicit Lagrangian twin support vector regression by Newton method [PDF]
International Journal of Computational Intelligence Systems, 2014 In this work, an implicit Lagrangian for the dual twin support vector regression is proposed. Our formulation leads to determining non-parallel –insensitive down- and up- bound functions for the unknown regressor by constructing two unconstrained ...
S. Balasundaram, Deepak Gupta
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Co-regularised support vector regression [PDF]
, 2017 We consider a semi-supervised learning scenario for regression, where only few labelled examples, many unlabelled instances and different data representations (multiple views) are available. For this setting, we extend support vector regression with a co-
A Bender +6 more
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Cubist Regression, Random Forest and Support Vector Regression for Solar Power Prediction
Revue des Énergies Renouvelables, 2022 At a time when the energy transition is inescapable and artificial intelligence is rapidly advancing in all directions, solar renewable energy output forecasting is becoming a popular concept, especially with the availability of large data sets and the ...
Souhaila Chahboun, Mohamed Maaroufi
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European exchange trading funds trading with locally weighted support vector regression [PDF]
, 2017 In this paper, two different Locally Weighted Support Vector Regression (wSVR) algorithms are generated and applied to the task of forecasting and trading five European Exchange Traded Funds.
de la Fuente, David +3 more
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Forecasting bus passenger flows by using a clustering-based support vector regression approach [PDF]
, 2020 As a significant component of the intelligent transportation system, forecasting bus passenger flows plays a key role in resource allocation, network planning, and frequency setting.
Bai, Yun +3 more
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Support vector regression model for flight demand forecasting
International Journal of Engineering Business Management, 2023 Flight demand forecasting is a particularly critical component for airline revenue management because of the direct influence on the booking limits that determine airline profits.
Wei FAN +6 more
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Vector-Valued Support Vector Regression [PDF]
The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006 A vector-valued extension of the support vector regression problem is presented here. The vector-valued variant is developed by extending the notions of the estimator, loss function and regularization functional from the scalar-valued case. A particular emphasis is placed on the class of loss functions chosen which apply the epsiv-insensitive loss ...
openaire +1 more source
Incremental Sparse Density-Weighted Twin Support Vector Regression [PDF]
Jisuanji gongchengThe Density-Weighted Twin Support Vector Regression(DWTSVR) is a regression algorithm that reflects the internal distribution of data with high prediction accuracy and robustness.
Weijie DING, Binjie GU, Feng PAN
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