Related references
Note: Only part of the references are listed.Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
Weicong Kong et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
Robust Support Vector Regression in Primal with Asymmetric Huber Loss
S. Balasundaram et al.
NEURAL PROCESSING LETTERS (2019)
Sequential grid approach based support vector regression for short-term electric load forecasting
Youlong Yang et al.
APPLIED ENERGY (2019)
Vector field-based support vector regression for building energy consumption prediction
Hai Zhong et al.
APPLIED ENERGY (2019)
A new hybrid model to predict the electrical load in five states of Australia
Jinran Wu et al.
ENERGY (2019)
Parallel Computing of Support Vector Machines: A Survey
Shirin Tavara
ACM COMPUTING SURVEYS (2019)
Asymmetric nu-twin support vector regression
Yitian Xu et al.
NEURAL COMPUTING & APPLICATIONS (2018)
Residual value forecasting using asymmetric cost functions
Korbinian Dress et al.
INTERNATIONAL JOURNAL OF FORECASTING (2018)
Improving economic values of day-ahead load forecasts to real-time power system operations
Yamin Wang et al.
IET GENERATION TRANSMISSION & DISTRIBUTION (2017)
Boosted neural networks for improved short-term electric load forecasting
A. S. Khwaja et al.
ELECTRIC POWER SYSTEMS RESEARCH (2017)
An incremental electric load forecasting model based on support vector regression
YouLong Yang et al.
ENERGY (2016)
Minimizing asymmetric loss in medium-term wind power forecasting
Carsten Croonenbroeck et al.
RENEWABLE ENERGY (2015)
Asymmetric ν-tube support vector regression
Xiaolin Huang et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2014)
A Strategy for Short-Term Load Forecasting by Support Vector Regression Machines
Ervin Ceperic et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2013)
Robust Variable Selection With Exponential Squared Loss
Xueqin Wang et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2013)
Quantile regression for longitudinal data with a working correlation model
Liya Fu et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2012)
Short-Term Load Forecasting: Similar Day-Based Wavelet Neural Networks
Ying Chen et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2010)
Electric Load Forecasting Based on Locally Weighted Support Vector Regression
Ehab E. Elattar et al.
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS (2010)
TSVR: An efficient Twin Support Vector Machine for regression
Peng Xinjun
NEURAL NETWORKS (2010)
Quantile regression without the curse of unsmoothness
You-Gan Wang et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2009)
Asymmetrical interval regression using extended epsilon-SVM with robust algorithm
Shao-Qing Xu et al.
FUZZY SETS AND SYSTEMS (2009)
Statistical performance of support vector machines
Gilles Blanchard et al.
ANNALS OF STATISTICS (2008)
Generation of synthetic sequences of electricity demand: Application in South Australia
L. Magnano et al.
ENERGY (2007)
A tutorial on support vector regression
AJ Smola et al.
STATISTICS AND COMPUTING (2004)
Support vector machines for short-term electrical load forecasting
M Mohandes
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2002)
Variable selection via nonconcave penalized likelihood and its oracle properties
JQ Fan et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2001)
Neural networks for short-term load forecasting: A review and evaluation
HS Hippert et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2001)
Share Paper
