Recurrent Neural Networks for Short-Term Load Forecasting
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The article was published on 2017-01-01 and is currently open access. It has received 88 citations till now. The article focuses on the topics: Recurrent neural network & Term (time).read more
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Edge Machine Learning for AI-Enabled IoT Devices: A Review
TL;DR: A detailed review on models, architecture, and requirements on solutions that implement edge machine learning on Internet of Things devices is presented, with the main goal to define the state of the art and envisioning development requirements.
Journal ArticleDOI
Convolutional and recurrent neural network based model for short-term load forecasting
TL;DR: The results of experiments show the superiority of the proposed method compared to some recent works in the field of short-term load forecasting.
Journal ArticleDOI
Intelligent forecaster of concentrations (PM2.5, PM10, NO2, CO, O3, SO2) caused air pollution (IFCsAP)
TL;DR: The aim of this work is to build a programmable system capable of predicting the pollutant concentrations within the next 48 h called intelligent forecaster of concentrations caused air pollution (IFCsAP) and making the machine the primary source of information after these concentrations are collected and stored in real time.
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A Hybrid Deep Learning Model to Forecast Particulate Matter Concentration Levels in Seoul, South Korea
Guang Yang,HwaMin Lee,Giyeol Lee +2 more
TL;DR: In this paper, the authors proposed novel hybrid models to combine the strength of two types of deep learning methods (LSTM and gated recurrent unit) for air pollution forecasting.
Journal ArticleDOI
An artificial neural network-based forecasting model of energy-related time series for electrical grid management
TL;DR: An artificial neural network (ANN)-based model is investigated for short-term forecasting of the hourly wind speed, solar radiation, and electrical power demand, and the non-linear autoregressive network with exogenous inputs (NARX) ANN is considered, and then selected to perform multi-step-ahead forecasting.