相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。A high-accuracy hybrid method for short-term wind power forecasting
Sahra Khazaei et al.
ENERGY (2022)
Ridge regression ensemble of machine learning models applied to solar and wind forecasting in Brazil and Spain
Tatiane C. Carneiro et al.
APPLIED ENERGY (2022)
Multi-space collaboration framework based optimal model selection for power load forecasting
Huafeng Xian et al.
APPLIED ENERGY (2022)
Short-term electrical load forecasting through heuristic configuration of regularized deep neural network
Ashraful Haque et al.
APPLIED SOFT COMPUTING (2022)
Short-Term Load Forecasting Using Channel and Temporal Attention Based Temporal Convolutional Network
Xianlun Tang et al.
ELECTRIC POWER SYSTEMS RESEARCH (2022)
Efficient bootstrap stacking ensemble learning model applied to wind power generation forecasting
Matheus Henrique Dal Molin Ribeiro et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)
Applications of random forest in multivariable response surface for short-term load forecasting
Guo-Feng Fan et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)
A novel asynchronous deep reinforcement learning model with adaptive early forecasting method and reward incentive mechanism for short-term load forecasting
Wenyu Zhang et al.
ENERGY (2021)
A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting
Seyed Mohammad Jafar Jalali et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)
MPF-Net: A computational multi-regional solar power forecasting framework
Faiza Mehmood et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)
Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features
Lechen Li et al.
APPLIED ENERGY (2021)
Hybrid forecasting method for wind power integrating spatial correlation and corrected numerical weather prediction
Shuai Hu et al.
APPLIED ENERGY (2021)
Convolutional and recurrent neural network based model for short-term load forecasting
Hosein Eskandari et al.
ELECTRIC POWER SYSTEMS RESEARCH (2021)
Short-term load forecasting of industrial customers based on SVMD and XGBoost
Yuanyuan Wang et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2021)
The evaluation of reanalysis and analysis products of solar radiation for Sindh province, Pakistan
Zia ul Rehman Tahir et al.
RENEWABLE ENERGY (2020)
Energy management system for smart grid: An overview and key issues
Sumit K. Rathor et al.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2020)
A Framework of Using Machine Learning Approaches for Short-Term Solar Power Forecasting
Usman Munawar et al.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY (2020)
Accurate Deep Model for Electricity Consumption Forecasting Using Multi-Channel and Multi-Scale Feature Fusion CNN-LSTM
Xiaorui Shao et al.
ENERGIES (2020)
A Deep Neural Network-Assisted Approach to Enhance Short-Term Optimal Operational Scheduling of a Microgrid
Fatma Yaprakdal et al.
SUSTAINABILITY (2020)
DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series prediction
Yeqi Liu et al.
EXPERT SYSTEMS WITH APPLICATIONS (2020)
A Comparative Analysis of Machine Learning Approaches for Short-/Long-Term Electricity Load Forecasting in Cyprus
Davut Solyali
SUSTAINABILITY (2020)
A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons
Aneeque A. Mir et al.
SUSTAINABILITY (2020)
A Single Scalable LSTM Model for Short-Term Forecasting of Massive Electricity Time Series
Andres M. Alonso et al.
ENERGIES (2020)
Short-Term Load Forecasting of Microgrid via Hybrid Support Vector Regression and Long Short-Term Memory Algorithms
Arash Moradzadeh et al.
SUSTAINABILITY (2020)
High Accuracy Modeling for Solar PV Power Generation Using Noble BD-LSTM-Based Neural Networks with EMA
Youngil Kim et al.
APPLIED SCIENCES-BASEL (2020)
Short-Term Firm-Level Energy-Consumption Forecasting for Energy-Intensive Manufacturing: A Comparison of Machine Learning and Deep Learning Models
Andrea Maria N. C. Ribeiro et al.
ALGORITHMS (2020)
Regression tree ensembles for wind energy and solar radiation prediction
Alberto Torres-Barran et al.
NEUROCOMPUTING (2019)
Improved bidirectional extreme learning machine based on enhanced random search
Weipeng Cao et al.
MEMETIC COMPUTING (2019)
Integrating Long Short-Term Memory and Genetic Algorithm for Short-Term Load Forecasting
Arpita Samanta Santra et al.
ENERGIES (2019)
EA-LSTM: Evolutionary attention-based LSTM for time series prediction
Youru Li et al.
KNOWLEDGE-BASED SYSTEMS (2019)
Automatic hourly solar forecasting using machine learning models
Gokhan Mert Yagli et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)
Predicting residential energy consumption using CNN-LSTM neural networks
Tae-Young Kim et al.
ENERGY (2019)
Attention-based recurrent neural networks for accurate short-term and long-term dissolved oxygen prediction
Yeqi Liu et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)
Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting
Salah Bouktif et al.
ENERGIES (2019)
A feature learning approach based on XGBoost for driving assessment and risk prediction
Xiupeng Shi et al.
ACCIDENT ANALYSIS AND PREVENTION (2019)
Enhanced Deep Networks for short-Term and Medium-Term Load Forecasting
Lingyi Han et al.
IEEE ACCESS (2019)
A comparative study of LSTM neural networks in forecasting day-ahead global horizontal irradiance with satellite data
Shikhar Srivastava et al.
SOLAR ENERGY (2018)
Solar irradiation prediction with machine learning: Forecasting models selection method depending on weather variability
Alexis Fouilloy et al.
ENERGY (2018)
SVM hyperparameters tuning for recursive multi-step-ahead prediction
Jie Liu et al.
NEURAL COMPUTING & APPLICATIONS (2017)
Data driven prediction models of energy use of appliances in a low-energy house
Luis M. Candanedo et al.
ENERGY AND BUILDINGS (2017)
A novel hybrid model for hourly global solar radiation prediction using random forests technique and firefly algorithm
Ibrahim Anwar Ibrahim et al.
ENERGY CONVERSION AND MANAGEMENT (2017)
Daily global solar radiation estimation in desert areas using daily extreme temperatures and extraterrestrial radiation
A. Marzo et al.
RENEWABLE ENERGY (2017)
ARIMA-based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation
M. Hadi Amini et al.
ELECTRIC POWER SYSTEMS RESEARCH (2016)
Towards power plant output modelling and optimization using parallel Regression Random Forest
Jan Janousek et al.
SWARM AND EVOLUTIONARY COMPUTATION (2016)
Feature Selection of Time Series MODIS Data for Early Crop Classification Using Random Forest: A Case Study in Kansas, USA
Pengyu Hao et al.
REMOTE SENSING (2015)
An Enhanced k-Means Clustering Algorithm for Pattern Discovery in Healthcare Data
Ramzi A. Haraty et al.
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS (2015)
On-line learning of indoor temperature forecasting models towards energy efficiency
F. Zamora-Martinez et al.
ENERGY AND BUILDINGS (2014)
Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods
Pinar Tufekci
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2014)
Short, medium and long term load forecasting model and virtual load forecaster based on radial basis function neural networks
Changhao Xia et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2010)
A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data
Bjoern H. Menze et al.
BMC BIOINFORMATICS (2009)
Short term and medium term power distribution load forecasting by neural networks
T Yalcinoz et al.
ENERGY CONVERSION AND MANAGEMENT (2005)
分享论文
