Proposal of a flexible and universal survey generator for a Business Intelligence

The main objective of this study was to develop an evolutionary analysis of artificial neural networks (ANN) in the forecast of wind energy for the period from 2007 to 2021. T he SciMat software tool was used to identify the performance and impact measures of the main research topics. For this, 250 research articles were retrieved from the Scopus and Web of Science databases. For the first evaluated period (2007-2011), there is a greater use of ANN models for the forecasting of wind energy. In the second period (2012-2016), the forecast interval approa ches based on ANNs are used. Finally, in the third period (2017-2021 ) , hybrid approaches are proposed for forecasting wind energy using ANN models and other approaches. Therefore, the results indicate that this field of research is constantly evolving, without yet reaching its stage of scientific maturity. Furthermore, results show that renewable energy source is the basic and transversal cluster of the application of forecasting wind models.Keywords--Energy forecast; artificial neural networks (ANN); wind energy; bibliometric analysis; SciMat.

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“…+ Centralidad [13], [15]. Esta herramienta utiliza palabras conjuntas y el índice h para formar una base de conocimiento utilizando los…”

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Artificial Neural Networks in Forecasting Wind Energy: A Bibliometric Approach from 2007 to 2021

Zarate-Perez¹,

Grados²,

Rubiños³

et al. 2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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Proposal of a flexible and universal survey generator for a Business Intelligence

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Artificial Neural Networks in Forecasting Wind Energy: A Bibliometric Approach from 2007 to 2021

Artificial Neural Networks in Forecasting Wind Energy: A Bibliometric Approach from 2007 to 2021

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