基于深度学习的有效电力需求预测

Q4 Engineering

IEIE Transactions on Smart Processing and Computing Pub Date : 2021-12-31 DOI:10.5573/ieiespc.2021.10.6.483

Daegun Ko, Youngmin Yoon, Jinoh Kim, Haelyong Choi

引用次数: 1

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Effective Electricity Demand Prediction via Deep Learning

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来源期刊

IEIE Transactions on Smart Processing and Computing Engineering-Electrical and Electronic Engineering

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： IEIE Transactions on Smart Processing & Computing (IEIE SPC) is a regular academic journal published by the IEIE (Institute of Electronics and Information Engineers). This journal is published bimonthly (the end of February, April, June, August, October, and December). The topics of the new journal include smart signal processing, smart wireless communications, and smart computing. Since all electronic devices have become human brain-like, signal processing, wireless communications, and computing are required to be smarter than traditional systems. Additionally, electronic computing devices have become smaller, and more mobile. Thus, we call for papers sharing the results of the state-of-art research in various fields of interest. In order to quickly disseminate new technologies and ideas for the smart signal processing, wireless communications, and computing, we publish our journal online only. Our most important aim is to publish the accepted papers quickly after receiving the manuscript. Our journal consists of regular and special issue papers. The papers are strictly peer-reviewed. Both theoretical and practical contributions are encouraged for our Transactions.