A novel approach for forecasting global horizontal irradiance based on sparse quadratic RBF neural network-Reference-Cited by-同舟云学术

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A novel approach for forecasting global horizontal irradiance based on sparse quadratic RBF neural network

Published:2017-11 Issue: Volume:152 Page:266-280
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Jiang He^ORCID

Funder

National Natural Science Foundation of China

Scientific Research Fund of Jiangxi Provincial Education Department

National Science Foundation of Jiangxi, China

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference50 articles.

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2. An integrated artificial neural networks approach for predicting global radiation;Azadeh;Energy Convers Manage,2009

3. Solar irradiance forecasting at one-minute intervals for different sky conditions using sky camera images;Alonso-Montesinos;Energy Convers Manage,2015

4. Smart baseline models for solar radiation forecasting;Urraca;Energy Convers Manage,2016

5. A nonlinear support vector machine model with hard penalty function based on glowworm swarm optimization for forecasting daily global solar radiation;Jiang;Energy Convers Manage,2016

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