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03-01-2021

Generalized Regression Neural Network Model Based Estimation of Global Solar Energy Using Meteorological Parameters

Author: M. Sridharan

Published in: Annals of Data Science | Issue 4/2023

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Abstract

The global solar irradiance data plays a vital role in evaluating the performance of all the solar energy conversion devices. In general there are two methods to predict the performance of such irradiance, namely physical models and the machine learning models. This paper presents a generalized regression neural network model (a machine learning technique) for estimating the global solar irradiance using seasonal and meteorological factors as input parameters. Results obtained from this proposed generalized regression neural network approach are compared with the results estimated by extensively used machine learning based methodologies such as fuzzy and artificial neural network models. Such a comparative results clearly indicate that prediction accuracy of proposed generalized regression neural network model is in good agreement with experimentally measured values. The mean percentage error for using GRNN, fuzzy logic and artificial neural network are 3.55%, 4.64%, and 5.49%.

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Title: Generalized Regression Neural Network Model Based Estimation of Global Solar Energy Using Meteorological Parameters
Author: M. Sridharan
Publication date: 03-01-2021
Publisher: Springer Berlin Heidelberg
Published in: Annals of Data Science / Issue 4/2023
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-020-00319-4

A Case Study of Optimization of a Solar Power Plant Sizing and Placement in Madhya Pradesh, India Using Multi-Objective Genetic Algorithm

On Some Estimation Methods for the Inverse Pareto Distribution

Monitoring COVID-19 Cases and Vaccination in Indian States and Union Territories Using Unsupervised Machine Learning Algorithm

Wind Speed Prediction of Central Region of Chhattisgarh (India) Using Artificial Neural Network and Multiple Linear Regression Technique: A Comparative Study

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Generalized Regression Neural Network Model Based Estimation of Global Solar Energy Using Meteorological Parameters

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Other articles of this Issue 4/2023

A Case Study of Optimization of a Solar Power Plant Sizing and Placement in Madhya Pradesh, India Using Multi-Objective Genetic Algorithm

On Some Estimation Methods for the Inverse Pareto Distribution

Monitoring COVID-19 Cases and Vaccination in Indian States and Union Territories Using Unsupervised Machine Learning Algorithm

Wind Speed Prediction of Central Region of Chhattisgarh (India) Using Artificial Neural Network and Multiple Linear Regression Technique: A Comparative Study

A Generalized-Alpha–Beta-Skew Normal Distribution with Applications

A Machine Learning Approach and Methodology for Solar Radiation Assessment Using Multispectral Satellite Images

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Abstract

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Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

A Case Study of Optimization of a Solar Power Plant Sizing and Placement in Madhya Pradesh, India Using Multi-Objective Genetic Algorithm

On Some Estimation Methods for the Inverse Pareto Distribution

Monitoring COVID-19 Cases and Vaccination in Indian States and Union Territories Using Unsupervised Machine Learning Algorithm

Wind Speed Prediction of Central Region of Chhattisgarh (India) Using Artificial Neural Network and Multiple Linear Regression Technique: A Comparative Study

A Generalized-Alpha–Beta-Skew Normal Distribution with Applications

A Machine Learning Approach and Methodology for Solar Radiation Assessment Using Multispectral Satellite Images