4.7 Article

An Image Inpainting Approach to Short-Term Load Forecasting

Related references

Note: Only part of the references are listed.
Review Computer Science, Hardware & Architecture

Image inpainting based on deep learning: A review

Zhen Qin et al.

Summary: This article reviews the latest research status in the field of image inpainting based on deep learning, including inpainting methods of different neural network structures, technical improvement mechanisms, and comprehensive evaluation of model network structures and restoration methods. Future research directions include addressing current issues in image inpainting and driving continuous development in this field.

DISPLAYS (2021)

Article Economics

DeepAR: Probabilistic forecasting with autoregressive recurrent networks

David Salinas et al.

INTERNATIONAL JOURNAL OF FORECASTING (2020)

Article Computer Science, Information Systems

Enhanced Deep Networks for short-Term and Medium-Term Load Forecasting

Lingyi Han et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Multi-Scale Convolutional Neural Network With Time-Cognition for Multi-Step Short-Term Load Forecasting

Zhuofu Deng et al.

IEEE ACCESS (2019)

Article Engineering, Electrical & Electronic

Deep Learning for Household Load Forecasting-A Novel Pooling Deep RNN

Heng Shi et al.

IEEE TRANSACTIONS ON SMART GRID (2018)

Article Computer Science, Theory & Methods

An efficient deep model for day-ahead electricity load forecasting with stacked denoising auto-encoders

Chao Tong et al.

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING (2018)

Article Engineering, Electrical & Electronic

Short-Term Electricity Price Forecasting With Stacked Denoising Autoencoders

Long Wang et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2017)

Proceedings Paper Computer Science, Theory & Methods

Everything is Image: CNN-based Short-term Electrical Load Forecasting for Smart Grid

Liangzhi Li et al.

2017 14TH INTERNATIONAL SYMPOSIUM ON PERVASIVE SYSTEMS, ALGORITHMS AND NETWORKS & 2017 11TH INTERNATIONAL CONFERENCE ON FRONTIER OF COMPUTER SCIENCE AND TECHNOLOGY & 2017 THIRD INTERNATIONAL SYMPOSIUM OF CREATIVE COMPUTING (ISPAN-FCST-ISCC) (2017)

Proceedings Paper Business

Load Forecasting via Deep Neural Networks

Wan He

5TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, ITQM 2017 (2017)

Article Engineering, Electrical & Electronic

Forecasting electricity load by a novel recurrent extreme learning machines approach

Omer Faruk Ertugrul

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2016)

Article Economics

Probabilistic electric load forecasting: A tutorial review

Tao Hong et al.

INTERNATIONAL JOURNAL OF FORECASTING (2016)

Article Management

On the identification of sales forecasting models in the presence of promotions

Juan R. Trapero et al.

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY (2015)

Article Economics

A refined parametric model for short term load forecasting

Nathaniel Charlton et al.

INTERNATIONAL JOURNAL OF FORECASTING (2014)

Article Engineering, Electrical & Electronic

Short-Term Load Forecasting Based on a Semi-Parametric Additive Model

Shu Fan et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2012)

Article Statistics & Probability

Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing

Alysha M. De Livera et al.

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2011)

Article Engineering, Electrical & Electronic

Short-Term Load Forecasting Using Fuzzy Inductive Reasoning and Evolutionary Algorithms

V. H. Hinojosa et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2010)

Article Engineering, Electrical & Electronic

Load forecasting using support vector machines: A study on EUNITE competition 2001

BJ Chen et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2004)

Article Management

Short-term electricity demand forecasting using double seasonal exponential smoothing

JW Taylor

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY (2003)

Review Engineering, Electrical & Electronic

Neural networks for short-term load forecasting: A review and evaluation

HS Hippert et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2001)

Article Economics

The theta model: a decomposition approach to forecasting

V Assimakopoulos et al.

INTERNATIONAL JOURNAL OF FORECASTING (2000)